Senior Staff Product Manager - Data & AI

Role Description

We're looking for a Senior/Staff Product Manager to join our Data & Analytics team and own the product strategy for data platforms, analytics tooling, and AI-driven capabilities. This role sits at the intersection of data engineering, business strategy, and applied AI — you'll translate complex business needs into a clear product roadmap, while working hand-in-hand with data engineers to ship scalable, reliable, and high-impact solutions.

This is a high-visibility, cross-functional role for someone who can operate at both strategic and technical depth, partner effectively with engineering and business stakeholders, and has hands-on experience shipping AI/ML-powered products.

What You'll Do

• Product Management for Data, BI and AI product
  • Manage and execute the data analytics product vision to help business teams adopt data and use it confidently for decision-making.
  • Lead end-to-end delivery of AI-powered analytics products — from problem framing and data feasibility assessment through model evaluation, deployment, and adoption.
  • Define success metrics, build business cases, and prioritize a roadmap balancing technical debt, platform scalability, and business impact.
  • Provide statistical techniques, quantitative data analysis, predictive analytics, and scenario-based analysis to support product decisions.
• Cross-Functional Partnership
  • Engage with cross-functional business and IT teams to understand requirements, analyze, design, and help build solutions for analytics and data science products.
  • Partner closely with Data Engineering to design scalable data pipelines, infrastructure, and platform capabilities that support analytics and AI use cases.
  • Work directly with business partners (Sales, Marketing, Customer Success...) to identify high-value problems, gather requirements, and translate them into actionable product specs.
  • Collaborate closely with analysts and data scientists across the organization, including on model development, evaluation, and responsible AI practices (bias, explainability, governance).
  • Analyze complex requirements and translate them into simple, actionable user stories.
  • Maintain deep knowledge of cross-functional data and ensure data quality on all products launched.
• Delivery & Execution
  • Build dashboard prototypes to help business stakeholders visualize end products.
  • Get involved in testing analytic products for functionality, user interface, and data quality.
  • Provide technical support to business teams for self-serve analytics; define best practices and develop user guides.
  • Follow agile methodologies and deliver continuous enhancements to products.
  • Optimize release management to strike the right balance between business goals and delivery capacity.
  • Identify and manage risks in release delivery and communicate clearly with stakeholders, including mitigation plans.
  • Debug and identify root causes for critical issues and provide solution recommendations.
  • Ensure data security and compliance measures are in place for every product delivered.
• Leadership & Documentation
  • Support senior management by creating architecture, project management, and roadmap documentation.
  • Own the product lifecycle: discovery, prioritization, requirements, launch, and post-launch iteration.
  • Evangelize data-driven and AI-driven decision-making across the organization.
  • Mentor junior PMs and contribute to product process and best practices (especially at the Staff level).
  • Maintain a strong personal base of knowledge on data platform technology, industry practices, trends, and emerging issues.

Qualifications

• Master's Degree in Statistics, Analytics, Mathematics, Economics, or a related quantitative field (preferred).

Requirements

• 8+ years of product management experience (3+ years as a Data Analyst/similar role supporting cross-functional global business units, for candidates coming from an analytics background), with at least 2–3 years focused on data platforms, analytics, or AI/ML products.
• Demonstrated experience shipping AI/ML-powered features or products (e.g., recommendation systems, predictive models, LLM-based applications, automation tools) — this is required.
• Proven track record partnering closely with data engineering teams on data infrastructure, pipelines, or platform-level products.
• Experience working directly with business stakeholders to translate ambiguous needs into structured product requirements.
• Experience building customer-centric data products, sales-centric analytic products, and executive metrics/reporting.
• Experience with data from the Customer Experience and Sales domains.
• Experience in the data center domain and knowledge of data center products are nice-to-have.

Skills

• Strong technical fluency: comfortable discussing data architecture, ETL/ELT pipelines, data modeling, and ML/AI concepts with engineering teams.
• Strong statistical and data analysis skills, including regressions, classification, anomaly detection, and hypothesis testing, with experience applying these techniques in real analyses.
• Excellent communication and stakeholder management skills; able to flex between technical depth and business-level storytelling.
• Strong analytical skills in breaking down complex problems, processes, and systems to propose solutions.
• Ability to document and prototype business use cases and data flows.
• Strong quantitative skills; comfortable with SQL and interpreting data to drive decisions.
• Experience with agile product development practices, roadmap planning, and prioritization frameworks.
• Familiarity with the AI/ML lifecycle (data prep, model training/evaluation, deployment, monitoring) and responsible AI considerations.
• Proven experience building dashboards in Tableau, Power BI, QlikView, or similar tools.
• Ability to understand complex data models and connect to varied data sources such as SFDC, Exasol, Google BigQuery, and AWS.
• Tableau certification is desirable, along with experience on Tableau Online (cloud), Tableau Server, and Tableau Prep.

Nice to Have

• Prior experience as a data analyst, data engineer, or data scientist before transitioning into product.
• Experience with generative AI / LLM-based product development.