JPMorgan Chase & Co.

Data Scientist Associate

JPMorgan Chase & Co. Bengaluru, Karnataka, India

Financial Services · 10,001+ employees

7 h ago
data-scientist Mid (2-5 yrs) Full-time India
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About the role

Build and productionize end-to-end RAG and Agentic RAG applications for financial services use cases. Collaborate with stakeholders to translate requirements into features while ensuring security, privacy, and responsible AI standards.

What they look for

Python RAG Machine Learning Data Science Software Engineering SQL Pandas Spark LangChain LlamaIndex AWS Azure NLP Vector Databases Data Analysis CI/CD

Requirements

Requires 3+ years of experience in software engineering, applied ML, or data science. Proficiency in Python, RAG frameworks, SQL, and cloud platforms is essential for this role.

Full description

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Data Scientist Associate at JPMorganChase within the Asset and Wealth Management, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Build and productionize RAG and Agentic RAG applications for financial-services use cases (intelligent search, Q&A, summarization, and workflow assistants). This role blends core software engineering with applied data science skills—data cleaning, analytics, experimentation, and evaluation—to improve retrieval quality and model reliability.

Job Responsibilities

  • Build end-to-end RAG applications: document ingestion → parsing → chunking → embeddings → indexing → retrieval → grounded generation (with citations/attribution where applicable).
  • Implement Agentic RAG patterns (query planning, multi-hop retrieval, tool-based lookups, reranking, guardrails, and fallback behaviors) for complex user questions.
  • Develop LLM-based NLP capabilities for classification, extraction, summarization, semantic search, and conversational flows tailored to financial domain needs.
  • Perform data preparation and quality work: cleaning noisy text, de-duplication, normalization, metadata enrichment, labeling, and maintaining curated datasets for evaluation/training.
  • Run applied data science experiments to improve relevance and answer quality: A/B tests, prompt/retrieval experiments, embedding model comparisons, chunking strategy tests, and reranker evaluations.
  • Define and track quality metrics across retrieval and generation (e.g., recall@k, MRR, precision, groundedness, citation coverage, user satisfaction proxies) and create lightweight dashboards/regular reporting.
  • Build basic analytics pipelines around usage and quality signals (feedback, clicks, escalation rates, latency/cost) to guide iteration.
  • Implement testing and evaluation harnesses: golden question sets, automated regression tests, adversarial prompts, and safety checks to reduce hallucinations.
  • Collaborate with product/design/stakeholders to translate requirements into shipped features and iterate quickly based on feedback.
  • Ensure solutions follow security, privacy, and responsible AI requirements (safe handling of sensitive data, access control-aware retrieval, logging/audit needs).

Required qualifications, capabilities and skills

  • 3+ years experience in software engineering, applied ML, data science engineering, or a related role building production systems.
  • Strong programming in Python , with APIs and services.
  • Working knowledge of applied data science fundamentals: data cleaning, exploratory data analysis (EDA), basic statistics, evaluation design, and communicating results.
  • Experience with RAG development using frameworks such as LangChain/LlamaIndex (or equivalent),
  • Comfortable with SQL and data tooling (e.g., pandas / Spark basics) to prepare datasets and run analyses.
  • Experience with cloud (AWS or Azure) and standard SDLC practices (version control, CI/CD basics, testing).

Preferred qualifications, capabilities and skills

  • Exposure to vector databases/search (e.g., OpenSearch/Elastic, Pinecone, Weaviate, FAISS) and reranking approaches.
  • Experience with evaluation frameworks (offline relevance labeling, LLM-as-judge with guardrails, regression suites) and basic experiment design.
  • Familiarity with agent frameworks (LangGraph/Semantic Kernel/etc.) and Agentic RAG workflows.
  • Experience with Python.
  • Familiarity with embeddings and retrieval concepts.

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. 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. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

J.P. Morgan Asset & Wealth Management delivers industry-leading investment management and private banking solutions. Asset Management provides individuals, advisors and institutions with strategies and expertise that span the full spectrum of asset classes through our global network of investment professionals. Wealth Management helps individuals, families and foundations take a more intentional approach to their wealth or finances to better define, focus and realize their goals.​

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