Senior Product Associate, ML Products

JPMorgan Chase & Co.; Palo Alto (CA); In loco; USD 110.000 - 160.000; Tempo pieno

Descrizione del lavoro

JPMorgan Chase & Co. in Palo Alto seeks a Senior Product Associate for the Personalization & Customer Insights team to drive ML-powered customer data insights and personalized experiences.

You will translate research into clear requirements and collaborate with Data Scientists and ML Engineers across a matrixed organization. This role covers end-to-end product delivery, experimentation, KPI tracking, and ensuring privacy, consent, and fairness.

Competenze

• 3+ years of product management, analytics, data science, or related roles.
• Strong data literacy and analytical judgment.
• Experience querying data with SQL and/or Python.
• Solid product fundamentals and agile delivery.
• Clear written and verbal communication; cross-functional collaboration.
• Ability to operate in ambiguity and learn quickly.

Mansioni

• Support the product roadmap and maintain a well-groomed backlog.
• Translate research and analytics into clear requirements, tradeoffs, and decisions.
• Partner with Data Scientists and ML Engineers across the model lifecycle.
• Help define hypotheses and support experiments (e.g., A/B tests).
• Track KPIs for engagement, quality, and reliability; translate results into next steps.
• Coordinate with Design, Engineering, and partner teams for alignment and momentum.
• Support responsible AI, privacy, governance, and fairness with control functions.

Conoscenze

Product management

Analytics

Data science

Engineering

Agile delivery

SQL

Python

Written & verbal comms

Cross-functional collaboration

Formazione

Bachelor's degree in Engineering, Data Science, Business

Strumenti

Jira

SQL

Python

Descrizione del lavoro

Job description

As a Senior Product Associate on the Personalization & Customer Insights team, you will support the end-to-end lifecycle of machine-learning products that translate customer data into actionable insights and personalized experiences. You will represent customer and partner needs, translate research and analytics into clear requirements, and help drive delivery in close partnership with Data Scientists and ML Engineers across a matrixed organization.

This role spans (1) delivering proactive personalization and next-best-action experiences across key customer moments and channels (e.g., marketing and servicing), and (2) enabling partner teams to self-serve personalization and insights for their own use cases. You will help frame hypotheses, support experimentation to measure impact, and contribute to scalable, reliable delivery while upholding privacy, consent, and fairness standards.

Job responsibilities

• Support the product roadmap and maintain a well-groomed backlog (epics, user stories, refinement) for one or more personalization and customer-intelligence products.
• Translate user research, journey insights, and product performance metrics into clear requirements, tradeoffs, and decisions.
• Partner with Data Scientists and ML Engineers across the model lifecycle (problem framing, evaluation, deployment, monitoring, iteration).
• Help define hypotheses and support experiments (e.g., A/B tests) to validate impact and measure outcomes.
• Track KPIs for engagement, quality, and reliability; translate results into prioritized next steps.
• Coordinate across Design, Engineering, and partner teams to maintain alignment and delivery momentum.
• Support responsible AI and data practices, including privacy, consent, governance, and fairness, in partnership with relevant control functions.

Required qualifications, capabilities, and skills

• 3+ years of experience in product management, analytics, data science, engineering, or a comparable domain.
• Strong data literacy and analytical judgment; comfortable using metrics and evidence to make product decisions.
• Hands-on experience querying/analyzing data (e.g., SQL and/or Python) to support product discovery, measurement, and experimentation.
• Strong product fundamentals: problem discovery, requirements definition, backlog management, and agile delivery (e.g., Jira or similar tools).
• Clear written and verbal communication and strong cross-functional collaboration skills.
• Comfort operating in ambiguity, learning quickly, and moving across problem spaces.

Preferred qualifications, capabilities, and skills

• Exposure to AI/ML, personalization/recommendations, and/or experimentation in partnership with Data Science.
• Experience designing or analyzing A/B tests and interpreting outcomes.
• Familiarity with cloud delivery environments (e.g., AWS) and multi-channel customer experiences (mobile, web, servicing).
• Bachelor's degree in Engineering, Data Science, Business, or comparable field.
• Interest in digital-banking trends and in privacy, consent, and fairness considerations in AI.