Are you ready to shape the future of investment management with cutting-edge data science? At J.P. Morgan Asset Management, you’ll have the opportunity to create impactful solutions that support our ESG and Stewardship teams. You’ll collaborate with talented professionals, grow your expertise, and make a real difference in how we serve our clients. Join us to advance your career and work on meaningful projects in a dynamic, inclusive environment.

As a Senior Data Scientist in Asset Management’s Data Science team, you will design and implement machine learning solutions that enhance our ESG and Stewardship functions. You will work closely with stakeholders across stewardship, ESG, and engineering to build innovative tools from the ground up. Your technical expertise will drive impactful results, and you’ll play a key role in shaping our data science capabilities. You’ll thrive in a collaborative culture that values hands-on problem solving and continuous learning.

 

Job Responsibilities:

Collaborate with internal stakeholders to gather requirements and understand business needsDevelop technical solutions using LLMs for search, content extraction, and principles-based reasoningBuild comprehensive testing packages to ensure solution efficacy and stakeholder trustDesign technical architectures and solutions for scalable implementationPartner with engineering teams to deliver high-quality, scalable outputsStay current with developments in data science and become a subject matter expertCommunicate complex concepts and results to both technical and business audiences

 

Required Qualifications, Capabilities, and Skills:

Advanced degree in a quantitative or technical discipline, or significant practical industry experienceExperience applying NLP, LLM, and ML techniques to solve business problems such as semantic search, information extraction, question answering, summarization, personalization, classification, or forecastingAdvanced Python programming skills with experience writing production-quality codeStrong understanding of ML algorithms including clustering, decision trees, and gradient descentKnowledge of language models, prompt engineering, model finetuning, and domain adaptationFamiliarity with deep learning frameworks and their latest developmentsAbility to communicate complex concepts and results to technical and business audiences

 

Preferred Qualifications, Capabilities, and Skills:

Experience in Asset ManagementBusiness domain knowledge in ESG, investment stewardship, proxy voting, corporate filings, or buyside investmentFamiliarity with model explainability and self-validation techniquesCFA or equivalent financial qualification