Senior Data Scientist
Key Responsibilities Own product and operational analytics across the platform, including retention , cohort behavior , funnel performance , and engagement .
Define and maintain the core metrics the company runs on, and make sure they mean the same thing to everyone.
Partner with Product and Engineering to instrument new features correctly and measure whether they worked.
Build analyses that answer open-ended operational questions, not just recurring reports.
Translate findings into clear recommendations for technical and non-technical audiences, including leadership.
Investigate anomalies in the data and drive them to root cause.
Build and maintain the dashboards, models, and data hygiene practices that make analysis repeatable.
Requirements
3+ years of experience in data science or analytics, ideally in a product-driven environment.
BS or equivalent, with a track record of strong analytical and logical reasoning.
Demonstrated depth in product or operational analytics: retention analysis , cohort analysis , funnel and engagement measurement .
Strong SQL and fluency in Python or R for analysis.
Genuine problem-solving orientation. You are comfortable with ambiguous questions and can define the analysis yourself.
Excellent communication and storytelling. You can walk through a problem you solved, the approach you chose, and why, and make it land with a non-technical audience.
Comfort operating in a fast-moving startup where the question changes before the dashboard is finished.
Nice to Have
Experience in healthcare , digital health , or another regulated data environment.
Experience building analytics infrastructure from an early stage.
Work Environment
NYC HQ preferred . Remote is possible for exceptional candidates.
We have video on for our weekly team syncs and technical discussions. Camera is required to be on during meetings.
Own product and operational analytics across the platform, including retention , cohort behavior , funnel performance , and engagement .
Define and maintain the core metrics the company runs on, and make sure they mean the same thing to everyone.
Partner with Product and Engineering to instrument new features correctly and measure whether they worked.
Build analyses that answer open-ended operational questions, not just recurring reports.
Translate findings into clear recommendations for technical and non-technical audiences, including leadership.
Investigate anomalies in the data and drive them to root cause.
Build and maintain the dashboards, models, and data hygiene practices that make analysis repeatable.
3+ years of experience in data science or analytics, ideally in a product-driven environment.
BS or equivalent, with a track record of strong analytical and logical reasoning.
Demonstrated depth in product or operational analytics: retention analysis , cohort analysis , funnel and engagement measurement .
Strong SQL and fluency in Python or R for analysis.
Genuine problem-solving orientation. You are comfortable with ambiguous questions and can define the analysis yourself.
Excellent communication and storytelling. You can walk through a problem you solved, the approach you chose, and why, and make it land with a non-technical audience.
Comfort operating in a fast-moving startup where the question changes before the dashboard is finished.
Experience in healthcare , digital health , or another regulated data environment.
Experience building analytics infrastructure from an early stage.
NYC HQ preferred . Remote is possible for exceptional candidates.
We have video on for our weekly team syncs and technical discussions. Camera is required to be on during meetings.
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