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Staff Data Scientist | Analytics

Machinify · Remote - US · Remote · Active · Greenhouse

Job facts

FieldValue
CompanyMachinify
TitleStaff Data Scientist | Analytics
Normalized title-
Department / teamData Science
LocationUnited States
Work modelRemote / Remote
Employment typeFull Time
Salary-
Statusactive
ATS providerGreenhouse
Posted / first seen2026-03-17 / 2026-05-29
Changed / last seen2026-05-29 / 2026-06-06

Related slices

PageWhat it containsOpen
Company jobsActive postings from Machinify.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Greenhouse.Open
Provider filtered searchThe same provider as a filtered job collection.Open
Department jobsActive postings in Data Science.Open
Work model jobsActive Remote postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyMachinify
Source21b206a0-4e55-4c82-8ff8-b54876e4ec8c
ATS providerGreenhouse

Description

Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 85 health plans, including many of the top 20, and representing more than 270 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise. We’re constantly reimagining what’s possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs. What You'll Do Independently partner with business stakeholders to understand complex operational challenges, build domain context, and frame analytical approaches — without predefined solutions or heavy direction Perform deep exploratory data analysis across payment operations, chart review workflows, and customer performance metrics to diagnose root causes and identify optimization opportunities Build and maintain dashboards and reporting infrastructure that give leaders real-time visibility into operational and financial performance Conduct business reviews including month-to-month bridges, waterfall analyses, and price-volume-mix decompositions to explain performance variance Use LLMs and AI-assisted tools (e.g., Claude, GPT) for data exploration, pattern identification, and accelerating analytical workflows Translate ambiguous business questions into structured analytical approaches with clear, actionable recommendations Work with both models and querying to understand problems — diagnosing first, then standardizing and building scalable solutions Partner cross-functionally with Product, Data Science, Engineering, and Operations teams to deliver analytics-ready solutions Build foundational data assets — base data sets, aggregates, and pipelines — required for robust reporting and insight generation What You Bring 4-6 years of experience in product analytics OR a high-level business analytics role (quantifying product/business impact, translating data/insights/KPI into business decisions, showing impact using data and analysis, translating complex data analysis into stories to influence business decisions, etc.) Strong proficiency in SQL and Python for data manipulation, analysis, and visualization Demonstrated ability to independently diagnose complex business problems through exploratory data analysis — comfortable working without predefined solutions Experience with BI/visualization tools (e.g., Power BI, Tableau, Looker) and building dashboards for business stakeholders Familiarity with LLMs and AI tools for data analysis — comfortable using AI-assisted workflows to accelerate insight generation and excited to push the boundaries of what's possible Degree in a quantitative field (e.g., Economics, Statistics, Operations Research, Data Science, Engineering, or related discipline) Strong communication and storytelling skills — ability to work directly with senior stakeholders and present complex findings clearly to both technical and non-technical audiences Experience working with large-scale data warehouses (Databricks, Snowflake, BigQuery, or similar) Consulting mindset: ability to quickly build business context in unfamiliar domains, structure ambiguous problems, and deliver actionable recommendations Curiosity, growth mindset, and excitement about learning new areas — including healthcare, LLMs, and GenAI Comfort operating in a fast-paced, ambiguous environment and balancing short-term deliverables with longer-term strategic work Nice-to-Haves Background in management consulting or strategic advisory (McKinsey, BCG, Bain, Deloitte, or similar) Economics background with understanding of causal reasoning and business impact measurement Experience in healthcare, payment integrity, or health insurance operations (or strong aptitude for quickly learning complex regulated domains) Experience with financial modeling and simulation — quantifying the impact of operational changes Familiarity with event-stream analytics and user behavior analysis Experience with dbt, Airflow, or similar data pipeline tools What We Offer Work from anywhere in the US! Machinify is digital-first. Top Medical/Dental/Vision offerings FSA/HSA Tuition reimbursement Competitive salary, 401(k) with company match Unlimited PTO Additional health and wellness benefits and perks Flexible and trusting environment where you’ll feel empowered to do your best work The salary for this position is based on an array of factors unique to each candidate: Such as years and depth of experience, set skills, certifications, etc. We are hiring for different levels and the base salary can range from $180k-$240k+ based on your assessed level. Compensation also includes meaningful equity, healthcare, unlimited PTO, and more. Equal Employment Opportunity at Machinify We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace. Machinify is an employment at will employer. We participate in E-Verify as required by applicable law. In accordance with applicable state laws, we do not inquire about salary history during the recruitment process. If you require a reasonable accommodation to complete any part of the application or recruitment process, please let our recruiters know. See our Candidate Privacy Notice at: https://www.machinify.com/candidate-privacy-notice/

Full job record

Job IDa5ebefefc28141483c57e05339dc723b0082c0ec
Org IDf98f4c50-bb90-40d5-9ce4-233e819a9ac8
Source ID21b206a0-4e55-4c82-8ff8-b54876e4ec8c
Board ID21b206a0-4e55-4c82-8ff8-b54876e4ec8c
Providergreenhouse
Provider Job Key4185395009
TitleStaff Data Scientist | Analytics
Normalized Title
Statusactive
Activeyes
Location TextRemote - US
DepartmentData Science
Team
Employment TypeFull-time
Workplace Typeremote
Remote Policyremote
CountryUnited States
Region
City
Salary Raw
Salary Min
Salary Max
Salary Currency
Salary Period
Source URLhttps://job-boards.greenhouse.io/machinifyinc/jobs/4185395009
Apply URLhttps://job-boards.greenhouse.io/machinifyinc/jobs/4185395009
First Seen At2026-05-29 22:57:06Z
Last Seen At2026-06-06 19:33:01Z
Last Checked At2026-06-06 19:33:01Z
Last Changed At2026-05-29 22:57:06Z
Inactive At
Source Posted At2026-03-17 18:05:10Z
Source Updated At2026-04-04 22:14:14Z
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=greenhouse/board=machinifyinc/date=2026-06-06/2026-06-06T19-33-01-559Z-33d1382111212feddac870b802a4b68affc84182e83325400b7f2fe367ece74e.json
Event Fields
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  "last_changed_at": "2026-05-29T22:57:06.213Z",
  "active_status": "active"
}
Parsed Structured
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  "launch_scope": {
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  "salary_period": null,
  "workplace_type": "remote",
  "salary_currency": null
}
Extensions
{}
Native Structured
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      "name": "Data Science",
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  ],
  "company_name": "Machinify",
  "requisition_id": 4107449009,
  "first_published": "2026-03-17T14:05:10-04:00",
  "application_deadline": null
}
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