CCB Risk Modeling Data-Scientist Sr Associate Fraud Prevention
JPMorgan Chase · Posted Oct 23
Global banking, investment, credit card, mortgage, and asset management services
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About the role
The CCB Risk Modeling team at JPMorgan Chase builds firmwide capabilities to identify and prevent fraud using machine learning and cloud-based tools. This role is a hands-on data science position in an AWS environment focused on fraud prevention and risk management. It involves developing and deploying ML models, researching graph networks, agentic AI and LLMs, and building data pipelines and dashboards with Databricks and PySpark.
What you will do
- Develop, train, and deploy machine learning models for fraud prevention and risk management.
- Research and implement novel architectures, including Graph Networks, Agentic AI, and Large Language Models.
- Build and test AI agents, iterating designs to enhance functionality and user experience. Conduct rigorous testing to ensure reliability and effectiveness of AI solutions.
- Use tools like Databricks and PySpark to create data pipelines and dashboards that support AI-driven insights and decision-making.
- Monitor and optimize model performance in real-world environments, adapting to evolving fraud patterns.
- Lead technical strategy and guide analytical direction within the team, fostering a culture of innovation and continuous improvement.
- Mentor and support junior team members, sharing best practices and technical expertise.
- Collaborate with cross-functional teams—including product, engineering, and data science—to align modeling solutions with business objectives and firmwide priorities.
- Contribute to the development of scalable, reusable machine learning solutions and best practices that strengthen the firm’s overall fraud prevention capabilities.
Skills used in this role
What the employer is looking for
- Master’s degree in Computer Science, Mathematics, Statistics, Economics, or a related quantitative field, or equivalent work experience.
- Minimal 5-year of experience in developing and managing predictive risk models in financial institutions.
- Deep understanding of machine learning theory and algorithms, with hands-on experience in both classical and deep learning methods.
- Proficient in Python, SQL or PySpark with experience in deep learning frameworks such as PyTorch or TensorFlow, and classical machine learning tools like XGBoost or Scikit-learn.
- Knowledge of graph analytics including GSQL will be an added bonus.
- Experience working with large datasets and building data pipelines using Databricks, PySpark, or similar technologies.
- Experience working in AWS cloud environments.
- Ability to build and test AI agents, iterate designs, and conduct rigorous testing for reliability and effectiveness.
- Experience mentoring or coaching junior team members.
Preferred qualifications
- Experience or strong interest in Graph Analytics and Agentic AI.
- Knowledge of GSQL.
- Deep technical understanding of the mathematics behind algorithms, not just library usage.
- Product-first mindset, with a focus on the role models play in the user experience and overall product responsibility.
- Versatility in handling both tabular and non-tabular data using classical machine learning (e.g., trees/forests) and modern deep learning techniques.
- Driven by impact and energized by the responsibility of having your models make decisions on live financial transactions.
- Demonstrated ability to build scalable, reusable solutions that contribute to firmwide capabilities and long-term strategic goals.
Benefits and support
- Compensation and benefits are detailed in the job posting
About JPMorgan Chase
JPMorgan Chase & Co. is one of the oldest, largest, and most diversified financial services institutions in the world. Operating globally through the J.P. Morgan and Chase brands, the firm provides a comprehensive range of financial solutions including investment banking, consumer and commercial banking, transaction processing, and asset management. Serving millions of consumers and many of the world's most prominent corporate, institutional, and government clients, the company combines deep market expertise with extensive technological investments.
- Industry
- Banking
- Company size
- 320000+ employees
- Founded
- 1799
- Location
- New York, New York, USA
- Funding stage
- Public Company
Leadership
Chairman and Chief Executive Officer
Chief Financial Officer
Chief Operating Officer
Global Chief Information Officer
CEO, Asset & Wealth Management
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