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AWM, Marcus by Goldman Sachs, Data Scientist - Fraud Strategy, Analyst - Richardson, TX

The Goldman Sachs Group
$3 trillion in assets under supervision, AWM delivers innovative solutions across traditional public investing and alternative investments, with a focus on long-term performance and client success.

Marcus by Goldman Sachs

As

United States, Texas, Richardson
Mar 26, 2026

About the division

Asset & Wealth Management (AWM) offers an unparalleled opportunity at one of the world's leading financial institutions. We are committed to helping a diverse global client base-including mutual funds, hedge funds, pension plans, sovereign wealth funds, insurance companies, endowments, foundations, third-party wealth firms, and ultra-high-net-worth individuals-achieve their financial goals through strategic investment and advisory services. With over $3 trillion in assets under supervision, AWM delivers innovative solutions across traditional public investing and alternative investments, with a focus on long-term performance and client success.

Marcus by Goldman Sachs

As the online consumer banking business of Goldman Sachs, Marcus operates as a digital bank, providing high-yield savings accounts and Certificates of Deposit (CDs) directly to individual consumers. Marcus combines Goldman Sachs' 150+ years of expertise with intuitive digital experiences, focusing on value, transparency, and simplicity for its millions of customers, and is recognized as the largest pure online bank, delivering a fully digital experience without physical branches.

As part of this team you will be responsible for:



  • Analyzing large volumes of data leveraging advanced statistical techniques to uncover new fraud pattern, and perform deep qualitative and quantitative expert reviews
  • Designing and developing data driven fraud strategies and capabilities to control fraud losses for consumer centric money movement products
  • Leveraging supervised and unsupervised machine learning techniques to accurately identify high risk activities on the customer account.
  • Building new data features and data products to improve statistical fraud models
  • Identifying data signals to accurately distinguish between fraud and non-fraud activities
  • Identifying and evaluate new data sources to build effective fraud controls
  • Creating trend reports and analysis leveraging coding language and tools such as Python, PySpark, SQL, Snowflake, Databricks and Excel
  • Synthesizing current portfolio risk or trend data to support recommendation for action
  • Exploring and leveraging cloud based data science technologies to further enhance existing fraud controls
  • Measuring and monitoring the impact of designed risk controls on customers, and develop strategies to ensure a positive customer experience
  • Working closely with technology and capability partners to implement new data driven ideas and solutions


Basic Qualifications:



  • Bachelor's degree in Mathematics, Statistics, Economics, Finance, Engineering or a related field.
  • Proven experience with very large dataset using Big Data tools and platform (e.g., Python, Pyspark, Snowflake, Databricks, SQL)
  • Ability to efficiently derive key insights and signals from complex structured and unstructured data
  • Strong working knowledge of statistical techniques including regression, clustering, neural network and ensemble techniques
  • 2+ years of experience in fraud risk management, preferably in banking products such as savings, checking, certificate deposit, credit cards, etc.
  • Creativity to go beyond tools and comfort working independently on solutions
  • Demonstrated thought leadership, creative thinking and project management Skills


Preferred Qualifications:



  • Master's degree in Mathematics, Statistics, Economics, Finance, Engineering or a related field
  • Experience building quantitative data driven statistical strategies for a consumer checking and saving business
  • Familiarity with large-scale graph processing e.g. graph clustering and link prediction mathematical algorithm
  • Expertise in advanced machine learning techniques - ensemble techniques, reinforcement learning, deep neural network
  • Knowledge of fraud risk vendors and technology in consumer finance or digital services industry
  • Experience with consumer banking authentication tools and methodologies
  • Experience in reporting and data visualization tools to report on trends and analysis


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., 2026. All rights reserved.

Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.

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