Senior Product Manager, Data and Analytics
New
Based in the United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years
- Required Skills
- PythonSQLAgileProduct ManagementSnowflakePandasData analyticsLooker
Requirements
- Bachelor’s degree in a relevant field or equivalent professional experience.
- 5+ years of experience in product management, analytics, data products, or related roles.
- Proven experience delivering data products or analytics solutions in fast-paced, agile environments.
- Experience working with healthcare data or healthcare technology is preferred.
- Strong communication and collaboration skills, with the ability to connect technical teams and business stakeholders.
- Strong SQL and analytical skills with the ability to investigate data and contribute hands-on to analytics work.
- Experience gathering requirements, defining product requirements, and creating measurable acceptance criteria.
- Passion for solving real-world problems through data-driven products.
- Experience with relational databases, data pipeline technologies, and dashboarding tools such as Snowflake, Looker, Sigma, Tableau, or Power BI.
- Experience using Python, including libraries such as pandas, for data analysis.
- Ability to thrive in ambiguous environments and manage multiple priorities effectively.
- Strong understanding of iterative product development, experimentation, and outcome-based delivery.
Responsibilities
- Define and execute the data product strategy, aligning analytics initiatives with organizational goals and stakeholder needs.
- Partner with data engineers, analysts, and business stakeholders to prioritize, scope, and deliver high-value data products.
- Lead discovery efforts by engaging with internal and external stakeholders to understand challenges and identify opportunities.
- Translate business questions into clear product requirements, problem statements, acceptance criteria, and actionable deliverables.
- Manage the development and continuous improvement of dashboards, reports, pipelines, metrics, and analytics solutions.
- Drive iterative delivery practices by prioritizing outcomes, gathering feedback, and adapting solutions based on learnings.
- Define success metrics and measurement frameworks to evaluate clinical, operational, and financial impact.
- Use SQL and analytical skills to investigate data, improve reporting quality, and support data-driven decisions.
- Collaborate with engineering teams to ensure data reliability, quality, and performance.
- Monitor critical data workflows and help resolve issues affecting data accuracy or availability.
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