Senior Data Scientist, Recommendations
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The role
Partner with Product, Engineering, and ML to identify opportunities, frame hypotheses, define success metrics, and translate findings into actionable product recommendations.
Improve algorithms across retrieval, ranking, and personalization; strengthen offline/online evaluation and alignment.
Define and lead experimentation for a two-sided marketplace; drive meta-analyses and playbooks to uplevel reads and decision quality.
Build tools and dashboards to improve experiment readability and KPI monitoring; standardize templates and health checks for fast, reliable iteration.
Deliver executive-ready presentations and docs that clarify options, tradeoffs, risks, and expected business impact; mentor other data scientists.
Serve as a trusted partner for the team and advance practices in experimentation, causal inference, and model evaluation.
Improve algorithms across retrieval, ranking, and personalization; strengthen offline/online evaluation and alignment.
Define and lead experimentation for a two-sided marketplace; drive meta-analyses and playbooks to uplevel reads and decision quality.
Build tools and dashboards to improve experiment readability and KPI monitoring; standardize templates and health checks for fast, reliable iteration.
Deliver executive-ready presentations and docs that clarify options, tradeoffs, risks, and expected business impact; mentor other data scientists.
Serve as a trusted partner for the team and advance practices in experimentation, causal inference, and model evaluation.
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