Senior Product Manager, Data & AI Products
New
Based in IndiaFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 6 to 10+ years
- Required Skills
- SQLArtificial IntelligenceMachine LearningProduct ManagementData modeling
Requirements
- 6 to 10+ years of product management experience, including at least 3 years focused on data products, analytics platforms, AI solutions, or machine learning-driven products.
- Proven track record of successfully launching and scaling data-intensive products within complex enterprise environments.
- Experience collaborating with data engineering, analytics engineering, machine learning, or software engineering teams.
- Strong understanding of modern data ecosystems, including data warehouses, semantic layers, business intelligence tools, and data orchestration platforms.
- Technical fluency with data concepts, including SQL, data modeling, system architecture, and data platform design.
- Knowledge of generative AI, large language models (LLMs), retrieval-augmented generation (RAG), AI agents, and emerging AI technologies.
- Strong product discovery, user research, roadmap planning, and requirements definition capabilities.
- Experience establishing and tracking meaningful product metrics, adoption indicators, and business outcomes.
- Excellent stakeholder management and communication skills, with the ability to influence technical and non-technical audiences.
- Strong analytical thinking, strategic problem-solving abilities, and sound decision-making skills.
- Comfortable working in ambiguous, fast-evolving environments while balancing multiple priorities and trade-offs.
- Experience in financial services, fintech, capital markets, analytics, or data science environments is highly desirable.
- Familiarity with platforms such as Databricks, dbt, or similar modern data stack technologies is an advantage.
Responsibilities
- Define and execute the product strategy, roadmap, and vision for internal data products, analytics platforms, and AI-powered solutions.
- Lead the development and adoption of an AI-driven analytics assistant, driving product requirements, user workflows, governance frameworks, and measurable business outcomes.
- Own and enhance a portfolio of enterprise data products that support forecasting, financial planning, analytics, reporting, and operational decision-making.
- Partner with engineering, analytics, and data science teams to prioritize features, manage delivery timelines, and ensure successful product execution.
- Drive innovation in AI, machine learning, and data accessibility by identifying opportunities to improve efficiency, automation, and self-service analytics capabilities.
- Collaborate with stakeholders across finance, risk, operations, and executive leadership to gather requirements and align product initiatives with business goals.
- Establish product success metrics, monitor adoption and performance, and continuously optimize products based on user feedback and data insights.
- Support the evolution of semantic data layers, data governance practices, and certification processes to improve trust, consistency, and accessibility of enterprise data.
- Develop clear product documentation, business cases, and requirements that enable cross-functional teams to deliver high-quality solutions.
- Lead product discovery efforts, evaluate emerging technologies, and balance competing priorities to maximize business impact.
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