JPMorgan Data Scientist Associate Sr 

United States, Delaware, Wilmington 

193718244

As a Data Scientist Senior Associate within JPMorgan Chase Asset and Wealth Management you will drive the analytics book of work and be part of the cross-functional team to improve the operations experience for our customers. You will be responsible for working collaboratively across partners in the MLIO Product team: Product, Data, Finance, UX/UI Design & Software Engineering. You will have the opportunity to work on the end-to-end analytics: building and updating the business case, analysis scoping, hypothesis development, data gathering, performance analysis, generating insights and participating in developing presentations of findings.

Job Responsibilities:

• Perform big-data analysis and improve ML/AI models in both AWS and on-premises environments.
• Lead end-to-end projects to investigate and explain key performance drivers and business impacts. Identify customer interactions and events across a variety of channels to better understand customer journeys and friction points.
• Partner with cross-functional team lead to consolidate business assumptions with productionized data to validate hypotheses and identify production flaws.
• Create & present results to peers, executive leadership team and business partners.
• Proactively investigate issues and problems in data collection, model building and production phases.
• Document Python and SQL codebase, data, and model outputs in clear and concise way
• Work as a member of agile, digital, tribes or scrum teams to provide data and analytics support for new product development.

Required qualifications, capabilities, and skills:

• Bachelor Degree in Machine Learning (NLP, LLM), Economics, Data Analytics, Statistics, or a STEM related field
• Master Degree in Machine Learning (NLP, LLM), Economics, Data Analytics, Statistics, or a STEM related field
• 3+years Experience of work experience.
• Solid programming skills in Python and SQL.
• Strong writing and communication skills.
• Detail oriented problem-solver with time management capability.
• Hands-on team player with full of curiosity to operate in a self-directed manner.
• Work experience with Excel PivotTable, presentation PPT and data wrangling & visualization tools (e.g. Tableau, Alteryx, SQL server)
• Coursework in multivariate statistics, multiple regression, programming languages (Python, SQL, Spark), machine learning (NLP, LLM), data analytics & visualization.
• Work experience in AWS, Spark/EMR, Snowflake.

Preferred qualifications, capabilities, and skills:

• Extensive experience in consumer banking units such as operations, servicing, collections, or marketing.
• Solid understandings in multi-linear regression, logistic regression, and causal inference methods (DD/PM/NN).
• Deep knowledge in recommendation system, NLP, LLM, Re-enforcement learning or Deep Learning algorithms.
• Experience in big data ETL (structured/unstructured database)
• Communication skills, you would be able to develop and deliver concise presentations that clearly articulate challenges, actions and results for complex matters - creating clarity and a bias for action with key stakeholders. Candidate should be able to crisply synthesize data into actionable insights for executive leadership.