Job description

You enjoy shaping products that make a real difference for customers, and you thrive when you can learn fast and move across different problems. Join our dynamic team and make a meaningful impact by helping deliver high-quality products that resonate with clients. 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. Hands-on product manager for ML-powered personalization and intelligence, turn research and data into shippable features, run experiments, and partner with Data Science and Engineering to deliver measurable outcomes across channels, while upholding privacy, consent, and fairness.

Requirements

Must-haves

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.
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.

Nice-to-haves

Preferred qualifications, capabilities, and skills

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlaisqlpythonagilejiraaws

Platform: oracle-cloud
Effort: medium