Join JPMorgan Chase & Co. as a Data Scientist Associate within the Business Banking Data and Analytics Team. In this role, you will be instrumental in constructing predictive models and developing robust RAG pipelines. You will extract valuable insights from complex datasets to promote data-driven decision-making and build AI-based solutions to enhance technological and business efficiency.
What You'll Do
- Align ML problem definition with business objectives to ensure solutions address real-world needs.
- Design, develop, and manage prompt-based models on Large Language Models (LLMs) for complex financial services tasks.
- Architect and oversee the development of next-generation machine learning models and systems using cutting-edge technologies.
- Drive innovation in machine learning solutions, focusing on scalability, flexibility, and future-proofing.
- Promote software and model quality, integrity, and security throughout the organization.
- Architect and implement scalable AI Agents, Agentic Workflows, and GenAI applications for enterprise deployment.
- Integrate GenAI solutions with enterprise platforms using API-based methods.
- Establish validation procedures with Evaluation Frameworks, bias mitigation, safety protocols, and guardrails.
- Collaborate with technology teams to lead the design and delivery of GenAI products.
What We're Looking For
- Formal training or certification in software engineering concepts and 5+ years of applied AI/ML experience.
- Strong understanding of the Software Development Life Cycle (SDLC), Data Structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, and Statistics.
- Experience with cloud platforms such as AWS, GCP, or Azure.
- Proficiency in RDBMS, NoSQL databases, and prompt design.
- Demonstrated expertise in machine learning frameworks such as TensorFlow, PyTorch, pyG, Keras, MXNet, and Scikit-Learn.
- Proficient in building AI Agents (e.g., LangChain, LangGraph, AutoGen), integration of tools (e.g., API), and RAG-based solutions (e.g., open search), Knowledge Graphs (e.g., neo4J).
- Proven track record of building and scaling software and/or machine learning platforms in high-growth or enterprise environments.
- Exceptional ability to communicate complex technical concepts to both technical and non-technical audiences.
Technical Stack
- Cloud: AWS, GCP, Azure
- Databases: RDBMS, NoSQL
- ML Frameworks: TensorFlow, PyTorch, pyG, Keras, MXNet, Scikit-Learn
- AI Tools: LangChain, LangGraph, AutoGen
Team & Environment
You will be a key member of the Business Banking Data and Analytics Team, collaborating closely with technology teams to deliver impactful products.
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.
