Lead the development of data-intensive products, translate business needs into technical requirements, and analyze complex datasets to inform platform-level priorities and product decisions.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Job Description
Data Platform Product Manager
Fully remote CST hours; Mon-Fri, 40 hours per week
Pay: $50 per hour W2; Duration: 10 months to start (temp to hire role)
- The role will involve deep, hands on engagement with data science, engineering, and analytics teams, and increased responsibility for translating complex, data intensive capabilities into products that meet business goals
Responsibilities:
- Own the end to end lifecycle of data intensive products, including datasets, analytics outputs, and data services, from definition through delivery and ongoing refinement.
- Translate business needs into clear data and technical requirements, priorities, and acceptance criteria for delivery teams.
- Analyze complex datasets to identify patterns, risks, gaps, and opportunities that inform platform level priorities and product decisions.
- Support and contribute to product planning and strategy sessions, including data platform and analytics initiatives.
- Develop and maintain comprehensive product documentation, including data flows, dependencies, and assumptions where applicable.
- Facilitate collaboration across departments and with external stakeholders, particularly with technical and analytics teams.
- Aid in creating and adjusting the product roadmap based on market insights and data driven findings.
- Provide insights and recommendations during product lifecycle meetings, grounded in data analysis and platform performance.
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Qualifications
- Effective Communication: Proficient in conveying complex ideas and technical concepts to both technical and non technical audiences.
- Analytical Expertise: Strong ability to interpret complex datasets and translate insights into product decisions.
- Project Management: Ability to manage and lead smaller initiatives within technical or data focused product areas.
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