Sr Data Scientist I
Posted Updated
Description
Job Description
About the Role
The Senior Data Analyst I develops analytic solutions that provide transparency to and enable critical business decisions regarding panel health, sample performance, and operational efficiency. In this role, you will apply a strong mathematical and statistical background to build predictive and prescriptive models aimed at optimizing operational spending-specifically reducing panelist incentives and operational costs without impacting panel performance, data quality, or core KPIs. Additionally, you will play a key role in tool migration initiatives, decoding complex logic from legacy workflows and data pipelines and re-engineering them into modern analytics frameworks. The ideal candidate brings 5+ years of experience, exhibits excellent project leadership skills, and communicates complex statistical insights clearly across technical and non-technical stakeholders. Qualifications
Key Responsibilities
- Statistical Modeling Cost Optimization: Apply advanced statistical methods, rate forecasting, and predictive modeling to identify cost-saving opportunities across panel operations, specifically driving reductions in panelist incentive costs while maintaining data integrity and key performance metrics.
- Tool Migration Logic Decoding: Work closely with stakeholders to decode, reverse-engineer, and document complex business logic embedded within legacy workflows and data pipelines, successfully converting and migrating them into new analytics tools and console frameworks.
- Independent Project Leadership: Lead analytics projects independently from conception to deployment, managing project timelines, production support, and the delivery of business-critical solutions.
- Process Automation Tech Debt Reduction: Design, automate, and optimize analytics tools to better plan, predict, and monitor sample performance, significantly reducing tech debt associated with legacy architectures.
- Business Intelligence Insights: Conduct research and quantitative analysis using descriptive, prescriptive, and statistical methods to deliver actionable insights and executive dashboards for business stakeholders.
- Cross-Functional Collaboration Governance: Collaborate with cross-functional teams to align analytics workflows, implement data governance processes, and ensure timely issue resolution and production delivery.
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