Data Scientist within Asset & Wealth Management (Senior Associate)

JPMAM Data Science is dedicated to enhancing and streamlining every stage of the investment process, from financial analysis and portfolio management to client services and advisory. We analyse extensive collections of data including financial documents, analyst reports, news articles, meeting notes, and client communications to empower data-driven decision making and process automation. We are seeking passionate data scientists who can apply the latest methodologies to generate real-time and actionable insights. 

The candidate must excel in working in a highly collaborative environment together with the business stakeholders, technologists, and control partners to deploy solutions into production. A strong passion for machine learning is essential, along with a commitment to continuous learning, research, and experimentation with new innovations in the field. Candidates should possess a solid understanding of modern NLP and/or financial knowledge, hands-on implementation experience, strong analytical thinking, and a keen interest in applying advanced analytics to solve complex problems in finance and asset management. 

Job Responsibilities 

Design and implement advanced techniques such as semantic search, retrieval-augmented generation (RAG), named entity recognition (NER), prompt engineering, and personalization for content extraction, search, question answering, reasoning, and recommendation. 

Develop LLM, NLP, and ML solutions that address client requirements and drive business transformation. 

Work closely with partner teams—including Business, Technology, Product Management, Strategy, and Business Management—to deploy and scale developed models in production environments. 

Build comprehensive testing setups to evaluate model performance and ensure efficacy and reliability. 

Communicate results effectively to business stakeholders through written reports, visualizations, and presentations. 

Stay current with the latest research in LLM, ML, and data science, and proactively identify and leverage emerging techniques to drive ongoing enhancement. 

Qualifications, Capabilities, and Skills 

Proven experience applying NLP, LLM, and ML techniques to solve high-impact business problems.  CFA designation or current pursuit of the CFA is highly desirable. Proficiency in programming languages such as Python and familiarity with machine learning libraries and frameworks. 

Excellent communication skills and ability to work collaboratively in a fast-paced, dynamic environment. 

Strong analytical skills with an understanding of financial markets and asset management.