Risk Management - Data Scientist Associate

JPMorgan Chase JPMorgan Chase · Banking · Jersey City, NJ +1 · Corporate Sector

Data Scientist Associate role focused on exploring, piloting, and implementing AI/ML solutions, including GenAI and agentic systems, within a large-scale enterprise fintech environment. The role involves developing production code, collaborating with stakeholders, ensuring Responsible AI compliance, and integrating models into operational workflows.

What you'd actually do

  1. Apply AI/ML techniques, including LLMs, Generative AI, and agentic systems to solve business problems, enhance product capabilities and accelerate development using coding assistants (e.g. Github Copilot).
  2. Write secure, high-quality production code, review and debug code, and contribute to documentation of code repositories and technical challenges.
  3. Collaborate with product, business, and cross-functional teams to define project goals, requirements, and plans, participating in stakeholder-facing communications as needed and assist in designing experiments, implementing algorithms, validating results, and productionizing trustworthy, explainable AI/ML solutions.
  4. Partner with Model Risk and Compliance stakeholders to ensure AI/ML solutions adhere to firmwide Responsible AI standards, including model documentation, bias and fairness testing, and appropriate human-in-the-loop controls.
  5. Deliver projects using Agile/sprint methodologies, translating business requirements into technical specifications, and supporting milestone achievement.

Skills

Required

  • 3+ years experience in Data Science or related field
  • Bachelor’s or Master’s degree in engineering, computer science, statistics, mathematics or similar technical or quantitative field with minimum 3 years' of relevant work experience.
  • Proven track record of deploying, AI, ML, and advanced analytics models in a large-scale enterprise environment.
  • Experience in AI/ML algorithms, statistical modeling, and scalable data processing pipelines.
  • Familiarity with machine learning frameworks (Tensorflow, Pytorch, Scikit-Learn, etc.) and agentic workflows and frameworks (LangChain, LangGraph, Auto-GPT).
  • Strong written and verbal communication skills, with the ability to convey technical concepts and results to both technical and business audiences
  • Scientific mindset with the ability to innovate and work both independently and collaboratively within a team.
  • Ability to thrive in a matrix environment and build partnerships with colleagues at various levels and across multiple locations.

What the JD emphasized

  • Proven track record of deploying, AI, ML, and advanced analytics models in a large-scale enterprise environment.
  • Partner with Model Risk and Compliance stakeholders to ensure AI/ML solutions adhere to firmwide Responsible AI standards, including model documentation, bias and fairness testing, and appropriate human-in-the-loop controls.

Other signals

  • Implement AI/ML solutions in a large-scale enterprise environment
  • Develop and deploy GenAI and agentic systems
  • Ensure adherence to Responsible AI standards