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Lead Data Scientist, Technology
Hdbt Fa Us2 Oraclecloud Com CX 1 · Orlando, FL, United States · Hybrid · Active · Oracle Recruiting Cloud / Fusion HCM
Job facts
| Field | Value |
|---|---|
| Company | Hdbt Fa Us2 Oraclecloud Com CX 1 |
| Title | Lead Data Scientist, Technology |
| Normalized title | - |
| Department / team | Information Technology |
| Location | Orlando, FL, United States |
| Work model | Hybrid / Hybrid |
| Employment type | Full Time |
| Salary | - |
| Status | active |
| ATS provider | Oracle Recruiting Cloud / Fusion HCM |
| Posted / first seen | 2026-05-21 / 2026-05-31 |
| Changed / last seen | 2026-06-06 / 2026-06-21 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Hdbt Fa Us2 Oraclecloud Com CX 1. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Oracle Recruiting Cloud / Fusion HCM. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in Orlando. | Open |
| Department jobs | Active postings in Information Technology. | Open |
| Work model jobs | Active Hybrid postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Hdbt Fa Us2 Oraclecloud Com CX 1 |
| Source | 7fa4bb2e-ec1f-49f2-80e1-8c85a5e766ee |
| ATS provider | Oracle Recruiting Cloud / Fusion HCM |
Description
Description
The Lead Data Scientist is responsible for designing, developing, and deploying production-ready data science and machine learning solutions that drive measurable business outcomes. This role operates as a senior individual contributor and technical lead, partnering closely with business, data, engineering, and platform teams to translate complex problems into scalable analytical solutions.
The position owns the full lifecycle of modeling initiatives, from problem definition and model development through deployment, monitoring, and continuous improvement. This role also helps establish standards, best practices, and repeatable patterns to mature enterprise data science capabilities.
Responsibilities
Design and develop statistical, machine learning, forecasting, and optimization models
Apply techniques such as regression, classification, clustering, time series, and anomaly detection
Translate business problems into scalable analytical approaches and measurable outcomes
Evaluate model performance, accuracy, stability, and business impact
Lead models from concept through production deployment and ongoing optimization
Partner with engineering teams to operationalize models into applications and workflows
Define and support model lifecycle processes, including versioning, monitoring, and retraining
Build reusable, maintainable, and well-documented modeling pipelines
Monitor model performance, drift, and usage; troubleshoot production issues as needed
Collaborate with stakeholders to define objectives, constraints, and success metrics
Identify and prioritize high-value data science opportunities
Communicate results, assumptions, risks, and recommendations clearly to technical and non-technical audiences
Support adoption by ensuring outputs are actionable, interpretable, and aligned to business needs
Perform exploratory data analysis to identify patterns and opportunities
Assess data quality, completeness, and suitability for modeling
Design and validate features that improve model performance
Partner with data teams to enhance analytical datasets and reusable data products
Apply and promote best practices for reproducibility, model governance, and responsible AI
Ensure alignment with enterprise standards for security, privacy, and compliance
Mentor data scientists and analysts on modeling techniques and production readiness
Lead technical and model reviews and contribute to data science standards and frameworks
Additional knowledge and skills:
Experience with machine learning and statistical libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow)
Familiarity with modern data platforms (e.g., Databricks, Snowflake, BigQuery)
Experience with cloud environments (AWS, Azure, or GCP)
Understanding of MLOps practices (model versioning, CI/CD, monitoring, lifecycle management)
Experience building reusable modeling pipelines or scalable data science solutions
Familiarity with tools such as MLflow, Git, and workflow orchestration platforms
Exposure to model governance and responsible AI practices
Experience with forecasting, optimization, pricing, or operational analytics is a plus
Exposure to generative AI or LLM-based solutions is a plus
Experience working in enterprise or matrixed environments is a plus
Qualifications
7+ years of experience in data science, machine learning, statistics, or a related field
Advanced degree in a quantitative field (preferred)
Proven experience developing and deploying models in production environments
Experience leading complex analytical initiatives from problem definition through adoption
Strong proficiency in Python and/or R for modeling and production-quality code
Strong SQL skills for data exploration and dataset development
Experience working in cross-functional environments (engineering, analytics, business teams)
Ability to communicate complex concepts to non-technical stakeholders
Company
With more than 225 locations worldwide, Signature Aviation is the largest global network of private aviation terminals, delivering safe, convenient, and elevated experiences to those we serve. As a premier hospitality organization and a certified Great Place to Work™, we are committed to redefining private air travel. Our nearly 6,000-strong team of aviation experts and enthusiasts is dedicated to delivering excellence to our guests and communities, and it starts with taking care of our team. Signature provides a variety of benefits, programs, and resources to support our team members’ overall well-being and professional development. We proudly volunteer and give back, focusing on elevating the neighborhoods where we operate, empowering the next generation of aviation professionals, and supporting our veterans.
From your health to your financial wellness, there are several benefits for you and your family when joining Signature Aviation.
Our Benefits:
Medical/prescription drug, dental, and vision Insurance
Health Savings Account
Flexible Spending Accounts
Life Insurance
Disability Insurance
401(k)
Critical Illness, Hospital Indemnity and Accident Insurance
Identity Theft and Legal Services
Paid time off
Paid Maternity Leave
Tuition reimbursement
Training and Development
Employee Assistance Program (EAP) & Perks
Qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, or other protected characteristics.
Full job record
| Job ID | 6b489a0ced5eba052a64b1977ebb1b0d23e55578 |
| Org ID | 731d8848-93c7-443a-ad64-339b31063c76 |
| Source ID | 7fa4bb2e-ec1f-49f2-80e1-8c85a5e766ee |
| Board ID | 7fa4bb2e-ec1f-49f2-80e1-8c85a5e766ee |
| Provider | oracle_hcm |
| Provider Job Key | 16530 |
| Title | Lead Data Scientist, Technology |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | Orlando, FL, United States |
| Department | Information Technology |
| Team | — |
| Employment Type | full_time |
| Workplace Type | hybrid |
| Remote Policy | hybrid |
| Country | United States |
| Region | FL |
| City | Orlando |
| Salary Raw | Description The Lead Data Scientist is responsible for designing, developing, and deploying production-ready data science and machine learning solutions that drive measurable business outcomes. This role operates as a senior individual contributor and technical lead, partnering closely with business, data, engineering, and platform teams to translate complex problems into scalable analytical solutions. The position owns the full lifecycle of modeling initiatives, from problem definition and model development through deployment, monitoring, and continuous improvement. This role also helps establish standards, best practices, and repeatable patterns to mature enterprise data science capabilities. Responsibilities Design and develop statistical, machine learning, forecasting, and optimization models Apply techniques such as regression, classification, clustering, time series, and anomaly detection Translate business problems into scalable analytical approaches and measurable outcomes Evaluate model performance, accuracy, stability, and business impact Lead models from concept through production deployment and ongoing optimization Partner with engineering teams to operationalize models into applications and workflows Define and support model lifecycle processes, including versioning, monitoring, and retraining Build reusable, maintainable, and well-documented modeling pipelines Monitor model performance, drift, and usage; troubleshoot production issues as needed Collaborate with stakeholders to define objectives, constraints, and success metrics Identify and prioritize high-value data science opportunities Communicate results, assumptions, risks, and recommendations clearly to technical and non-technical audiences Support adoption by ensuring outputs are actionable, interpretable, and aligned to business needs Perform exploratory data analysis to identify patterns and opportunities Assess data quality, completeness, and suitability for modeling Design and validate features that improve model performance Partner with data teams to enhance analytical datasets and reusable data products Apply and promote best practices for reproducibility, model governance, and responsible AI Ensure alignment with enterprise standards for security, privacy, and compliance Mentor data scientists and analysts on modeling techniques and production readiness Lead technical and model reviews and contribute to data science standards and frameworks Additional knowledge and skills: Experience with machine learning and statistical libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow) Familiarity with modern data platforms (e.g., Databricks, Snowflake, BigQuery) Experience with cloud environments (AWS, Azure, or GCP) Understanding of MLOps practices (model versioning, CI/CD, monitoring, lifecycle management) Experience building reusable modeling pipelines or scalable data science solutions Familiarity with tools such as MLflow, Git, and workflow orchestration platforms Exposure to model governance and responsible AI practices Experience with forecasting, optimization, pricing, or operational analytics is a plus Exposure to generative AI or LLM-based solutions is a plus Experience working in enterprise or matrixed environments is a plus Qualifications 7+ years of experience in data science, machine learning, statistics, or a related field Advanced degree in a quantitative field (preferred) Proven experience developing and deploying models in production environments Experience leading complex analytical initiatives from problem definition through adoption Strong proficiency in Python and/or R for modeling and production-quality code Strong SQL skills for data exploration and dataset development Experience working in cross-functional environments (engineering, analytics, business teams) Ability to communicate complex concepts to non-technical stakeholders Company With more than 225 locations worldwide, Signature Aviation is the largest global network of private aviation terminals, delivering safe, convenient, and elevated experiences to those we serve. As a premier hospitality organization and a certified Great Place to Work™, we are committed to redefining private air travel. Our nearly 6,000-strong team of aviation experts and enthusiasts is dedicated to delivering excellence to our guests and communities, and it starts with taking care of our team. Signature provides a variety of benefits, programs, and resources to support our team members’ overall well-being and professional development. We proudly volunteer and give back, focusing on elevating the neighborhoods where we operate, empowering the next generation of aviation professionals, and supporting our veterans. From your health to your financial wellness, there are several benefits for you and your family when joining Signature Aviation. Our Benefits: Medical/prescription drug, dental, and vision Insurance Health Savings Account Flexible Spending Accounts Life Insurance Disability Insurance 401(k) Critical Illness, Hospital Indemnity and Accident Insurance Identity Theft and Legal Services Paid time off Paid Maternity Leave Tuition reimbursement Training and Development Employee Assistance Program (EAP) & Perks Qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, or other protected characteristics. |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://hdbt.fa.us2.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1/job/16530 |
| Apply URL | https://hdbt.fa.us2.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1/job/16530 |
| First Seen At | 2026-05-31 18:03:19Z |
| Last Seen At | 2026-06-21 12:42:45Z |
| Last Checked At | 2026-06-21 12:42:45Z |
| Last Changed At | 2026-06-06 11:30:18Z |
| Inactive At | — |
| Source Posted At | 2026-05-21 19:32:47Z |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=oracle_hcm/board=hdbt.fa.us2.oraclecloud.com|CX_1/date=2026-06-21/2026-06-21T12-42-29-772Z-854c5aa7854f0a233e95e7020b5660026ab54eb43fd4fc47d0185f9771a827fc.json |
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],
"ExternalResponsibilitiesStr": "<ul><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Design and develop statistical, machine learning, forecasting, and optimization models</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Apply techniques such as regression, classification, clustering, time series, and anomaly detection</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Translate business problems into scalable analytical approaches and measurable outcomes</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Evaluate model performance, accuracy, stability, and business impact</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Lead models from concept through production deployment and ongoing optimization</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Partner with engineering teams to operationalize models into applications and workflows</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Define and support model lifecycle processes, including versioning, monitoring, and retraining</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Build reusable, maintainable, and well-documented modeling pipelines</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Monitor model performance, drift, and usage; troubleshoot production issues as needed</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Collaborate with stakeholders to define objectives, constraints, and success metrics</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Identify and prioritize high-value data science opportunities</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Communicate results, assumptions, risks, and recommendations clearly to technical and non-technical audiences</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Support adoption by ensuring outputs are actionable, interpretable, and aligned to business needs</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Perform exploratory data analysis to identify patterns and opportunities</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Assess data quality, completeness, and suitability for modeling</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Design and validate features that improve model performance</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Partner with data teams to enhance analytical datasets and reusable data products</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Apply and promote best practices for reproducibility, model governance, and responsible AI</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Ensure alignment with enterprise standards for security, privacy, and compliance</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Mentor data scientists and analysts on modeling techniques and production readiness</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Lead technical and model reviews and contribute to data science standards and frameworks</p></li></ul><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\"><strong>Additional knowledge and skills:</strong></p><ul><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Experience with machine learning and statistical libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow)</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Familiarity with modern data platforms (e.g., Databricks, Snowflake, BigQuery)</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Experience with cloud environments (AWS, Azure, or GCP)</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Understanding of MLOps practices (model versioning, CI/CD, monitoring, lifecycle management)</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Experience building reusable modeling pipelines or scalable data science solutions</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Familiarity with tools such as MLflow, Git, and workflow orchestration platforms</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Exposure to model governance and responsible AI practices</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Experience with forecasting, optimization, pricing, or operational analytics is a plus</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Exposure to generative AI or LLM-based solutions is a plus</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Experience working in enterprise or matrixed environments is a plus</p></li></ul>",
"InternalResponsibilitiesStr": "<ul><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Design and develop statistical, machine learning, forecasting, and optimization models</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Apply techniques such as regression, classification, clustering, time series, and anomaly detection</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Translate business problems into scalable analytical approaches and measurable outcomes</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Evaluate model performance, accuracy, stability, and business impact</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Lead models from concept through production deployment and ongoing optimization</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Partner with engineering teams to operationalize models into applications and workflows</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Define and support model lifecycle processes, including versioning, monitoring, and retraining</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Build reusable, maintainable, and well-documented modeling pipelines</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Monitor model performance, drift, and usage; troubleshoot production issues as needed</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Collaborate with stakeholders to define objectives, constraints, and success metrics</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Identify and prioritize high-value data science opportunities</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Communicate results, assumptions, risks, and recommendations clearly to technical and non-technical audiences</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Support adoption by ensuring outputs are actionable, interpretable, and aligned to business needs</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Perform exploratory data analysis to identify patterns and opportunities</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Assess data quality, completeness, and suitability for modeling</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Design and validate features that improve model performance</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Partner with data teams to enhance analytical datasets and reusable data products</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Apply and promote best practices for reproducibility, model governance, and responsible AI</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Ensure alignment with enterprise standards for security, privacy, and compliance</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Mentor data scientists and analysts on modeling techniques and production readiness</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Lead technical and model reviews and contribute to data science standards and frameworks</p></li></ul><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\"><strong>Additional knowledge and skills:</strong></p><ul><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Experience with machine learning and statistical libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow)</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Familiarity with modern data platforms (e.g., Databricks, Snowflake, BigQuery)</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Experience with cloud environments (AWS, Azure, or GCP)</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Understanding of MLOps practices (model versioning, CI/CD, monitoring, lifecycle management)</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Experience building reusable modeling pipelines or scalable data science solutions</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Familiarity with tools such as MLflow, Git, and workflow orchestration platforms</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Exposure to model governance and responsible AI practices</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Experience with forecasting, optimization, pricing, or operational analytics is a plus</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Exposure to generative AI or LLM-based solutions is a plus</p></li><li><p style=\"-webkit-text-stroke-width: 0px; color: rgb(0, 0, 0); font-family: "Times New Roman"; font-size: medium; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;\">Experience working in enterprise or matrixed environments is a plus</p></li></ul>",
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