JPMorgan Chase & Co. is seeking a Senior Data Science Associate as an Applied AI Data Scientist. In this role, you will design, deploy, and scale large language model (LLM) agents that transform complex finance questions into trusted, actionable insights for our Asset & Wealth Management Finance organization.
What You'll Do
- Build production LLM agents for finance workflows using techniques like retrieval‑augmented generation (RAG), tool use, and multi‑step reasoning.
- Develop robust data and inference pipelines in Python and SQL; integrate agents with APIs, microservices, and BI applications.
- Implement evaluation frameworks and guardrails: offline and online tests, automatic metrics (factuality, grounding, hallucination rate), human‑in‑the‑loop reviews, and red‑team testing.
- Optimize for scale, latency, and cost across cloud environments; leverage vector databases and embeddings for efficient retrieval.
- Partner with Finance, Product, and Engineering to identify high‑value use cases; translate ambiguous problems into measurable outcomes.
- Apply solid ML engineering and MLOps practices including versioning, CI/CD, model registry, monitoring, and incident response.
- Document systems, deliver enablement materials, and upskill partners; contribute to standards for privacy, security, and model risk governance.
What We're Looking For
- 6+ years in data/ML roles, including 3+ years building and operating production ML applications; hands‑on experience with LLMs.
- Strong Python and SQL programming skills.
- Practical knowledge of RAG, prompt engineering, fine‑tuning, function/tool calling, and vector stores.
- Experience with cloud platforms (e.g., AWS, Azure, or GCP) and modern data stacks (e.g., Databricks or Snowflake).
- Familiarity with LLM frameworks and orchestration (e.g., LangChain or LlamaIndex) and REST/GraphQL API design.
- Proficiency in analytics and applied statistics; ability to design experiments and evaluate business impact.
- Excellent communication and stakeholder management; comfort working across Finance, Technology, and Operations.
Nice to Have
- Experience building multi‑agent systems, autonomous workflows, or task planners.
- Experience with PySpark or distributed compute.
- Knowledge of model safety, bias, and privacy techniques; experience with model risk management and governance.
- Exposure to observability tools (logging, tracing, telemetry) and A/B testing.
- Background integrating agents with BI/reporting and workflow tools; familiarity with Tableau or similar is a plus.
- Experience with GPUs/accelerators, containerization, and infrastructure‑as‑code.
Technical Stack
- Languages: Python, SQL, PySpark
- Core Technologies: LLMs, RAG, Vector databases
- Cloud & Platforms: AWS/Azure/GCP, Databricks/Snowflake
- Frameworks & APIs: LangChain/LlamaIndex, REST/GraphQL APIs
Benefits & Compensation
- Comprehensive health care coverage
- On-site health and wellness centers
- Retirement savings plan
- Backup childcare
- Tuition reimbursement
- Mental health support
- Financial coaching
We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans.
