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HomeCompaniesHdpc Fa Us2 Oraclecloud Com CX 3002Asset & Wealth Management - Quantitative Strategist - Associate - Dallas

Asset & Wealth Management - Quantitative Strategist - Associate - Dallas

Hdpc Fa Us2 Oraclecloud Com CX 3002 · Dallas, TX, United States · Deleted · Oracle Recruiting Cloud / Fusion HCM

Job facts

FieldValue
CompanyHdpc Fa Us2 Oraclecloud Com CX 3002
TitleAsset & Wealth Management - Quantitative Strategist - Associate - Dallas
Normalized title-
Department / teamAssociate
LocationDallas, TX, United States
Work model-
Employment type-
Salary-
Statusdeleted
ATS providerOracle Recruiting Cloud / Fusion HCM
Posted / first seen2026-04-15 / 2026-05-31
Changed / last seen2026-06-19 / 2026-06-17

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City jobsActive postings in Dallas.Open
Department jobsActive postings in Associate.Open
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Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyHdpc Fa Us2 Oraclecloud Com CX 3002
Source6c2fc4b4-b977-4fca-ad16-3207bde507b7
ATS providerOracle Recruiting Cloud / Fusion HCM

Description

Description About Goldman Sachs Wealth Management Across Wealth Management, Goldman Sachs helps empower clients and customers around the world to reach their financial goals. Our advisor-led wealth management businesses provide financial planning, investment management, banking, and comprehensive advice to a wide range of clients, including ultra-high net worth and high net worth individuals, as well as family offices, foundations and endowments, and corporations and their employees. Our consumer business provides digital solutions for customers to better spend, borrow, invest, and save. Across Wealth Management, our growth is driven by a relentless focus on our people, our clients and customers, and leading-edge technology, data, and design. Our quantitative strategists are at the cutting edge of our business and solve real-world problems through a variety of analytical methods. As a member of our team, you will utilize your training in mathematics, programming, and logical thinking to build quantitative models that drive success in our business. Your problem-solving talents and aptitude for innovation will help define your contributions and enable you to find solutions to a broad range of problems, in a dynamic, fast-paced environment. Responsibilities As a strategist on our PWM Risk Strats team, you will work closely with various teams including risk management and fraud strategy . You will combine quantitative techniques and industry knowledge to build best in class models and tools that streamline risk management, detect fraud at scale, enable optimized data-driven business decision making, and optimize profitability. Responsibilities include: Developing and deploying ML models for fraud and anomaly detection as well as business workflows enhancement Delivering risk metrics and quantitative analytics for financial and non-financial risks across wealth management Develop AI-led solutions to improve efficiency and accuracy in risk management. Building and maintaining robust and systematic risk management tools and reporting Collaborating on the design of new and existing strategies to address clients’ investment goals. Developing and maintaining risk management and portfolio analysis tools across multiple asset classes for senior management and portfolio managers. Building and maintaining infrastructure of Strategists’ analytical systems. Basic Qualifications Bachelor, Masters or Ph.D. in a quantitative or engineering field, e.g. mathematics, physics, quantitative finance, computational finance, computer science, engineering 1-3 years of experience in the job offered or related quantitative financial modeling and software development positions Programming and mathematical skills are required Creativity, problem-solving skills, and ability to communicate complex ideas to a variety of audiences A self-starter, should have ability to work independently as well as thrive in a team environment Excellent understanding of machine learning techniques and algorithms, such as gradient boosting decision trees, random forests, etc., is a plus Experience with building models using common data science toolkits, i.e., Python (Pandas, NumPy, Scikit-learn) and Spark Experience with prompt engineering, working with LLM models, and MCP. Previous work experience in: Utilizing statistical methods, including time-series and regression analysis; programming in object-oriented languages for efficient model implementations; manipulating data sets using relational databases and SQL Preferred Qualifications Excellent understanding of machine learning techniques and algorithms, such as gradient boosting decision trees, random forests, etc., is a plus Experience with building models using common data science toolkits, i.e., Python (Pandas, NumPy, Scikit-learn) and Spark Experience with prompt engineering, working with LLM models, and MCP. Previous work experience in: Utilizing statistical methods, including time-series and regression analysis; programming in object-oriented languages for efficient model implementations; manipulating data sets using relational databases and SQL ABOUT GOLDMAN SACHS At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers. We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html © The Goldman Sachs Group, Inc., 2021. All rights reserved. Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Veteran/Sexual Orientation/Gender Identity

Full job record

Job ID88830b707d2da7fc32d77660ee0a2b094b9035b2
Org IDbe11fab8-3f8a-45d7-b0b8-f801e8cc9e3b
Source ID6c2fc4b4-b977-4fca-ad16-3207bde507b7
Board ID6c2fc4b4-b977-4fca-ad16-3207bde507b7
Provideroracle_hcm
Provider Job Key168556
TitleAsset & Wealth Management - Quantitative Strategist - Associate - Dallas
Normalized Title
Statusdeleted
Activeno
Location TextDallas, TX, United States
DepartmentAssociate
Team
Employment Type
Workplace Type
Remote Policy
CountryUnited States
RegionTX
CityDallas
Salary RawDescription About Goldman Sachs Wealth Management Across Wealth Management, Goldman Sachs helps empower clients and customers around the world to reach their financial goals. Our advisor-led wealth management businesses provide financial planning, investment management, banking, and comprehensive advice to a wide range of clients, including ultra-high net worth and high net worth individuals, as well as family offices, foundations and endowments, and corporations and their employees. Our consumer business provides digital solutions for customers to better spend, borrow, invest, and save. Across Wealth Management, our growth is driven by a relentless focus on our people, our clients and customers, and leading-edge technology, data, and design. Our quantitative strategists are at the cutting edge of our business and solve real-world problems through a variety of analytical methods. As a member of our team, you will utilize your training in mathematics, programming, and logical thinking to build quantitative models that drive success in our business. Your problem-solving talents and aptitude for innovation will help define your contributions and enable you to find solutions to a broad range of problems, in a dynamic, fast-paced environment. Responsibilities As a strategist on our PWM Risk Strats team, you will work closely with various teams including risk management and fraud strategy . You will combine quantitative techniques and industry knowledge to build best in class models and tools that streamline risk management, detect fraud at scale, enable optimized data-driven business decision making, and optimize profitability. Responsibilities include: Developing and deploying ML models for fraud and anomaly detection as well as business workflows enhancement Delivering risk metrics and quantitative analytics for financial and non-financial risks across wealth management Develop AI-led solutions to improve efficiency and accuracy in risk management. Building and maintaining robust and systematic risk management tools and reporting Collaborating on the design of new and existing strategies to address clients’ investment goals. Developing and maintaining risk management and portfolio analysis tools across multiple asset classes for senior management and portfolio managers. Building and maintaining infrastructure of Strategists’ analytical systems. Basic Qualifications Bachelor, Masters or Ph.D. in a quantitative or engineering field, e.g. mathematics, physics, quantitative finance, computational finance, computer science, engineering 1-3 years of experience in the job offered or related quantitative financial modeling and software development positions Programming and mathematical skills are required Creativity, problem-solving skills, and ability to communicate complex ideas to a variety of audiences A self-starter, should have ability to work independently as well as thrive in a team environment Excellent understanding of machine learning techniques and algorithms, such as gradient boosting decision trees, random forests, etc., is a plus Experience with building models using common data science toolkits, i.e., Python (Pandas, NumPy, Scikit-learn) and Spark Experience with prompt engineering, working with LLM models, and MCP. Previous work experience in: Utilizing statistical methods, including time-series and regression analysis; programming in object-oriented languages for efficient model implementations; manipulating data sets using relational databases and SQL Preferred Qualifications Excellent understanding of machine learning techniques and algorithms, such as gradient boosting decision trees, random forests, etc., is a plus Experience with building models using common data science toolkits, i.e., Python (Pandas, NumPy, Scikit-learn) and Spark Experience with prompt engineering, working with LLM models, and MCP. Previous work experience in: Utilizing statistical methods, including time-series and regression analysis; programming in object-oriented languages for efficient model implementations; manipulating data sets using relational databases and SQL ABOUT GOLDMAN SACHS At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers. We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html © The Goldman Sachs Group, Inc., 2021. All rights reserved. Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Veteran/Sexual Orientation/Gender Identity
Salary Min
Salary Max
Salary Currency
Salary Period
Source URLhttps://hdpc.fa.us2.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_3002/job/168556
Apply URLhttps://hdpc.fa.us2.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_3002/job/168556
First Seen At2026-05-31 18:05:01Z
Last Seen At2026-06-17 11:31:21Z
Last Checked At2026-06-19 11:39:49Z
Last Changed At2026-06-19 11:39:49Z
Inactive At2026-06-19 11:39:49Z
Source Posted At2026-04-15 20:13:37Z
Source Updated At
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