Senior Product Data Scientist
Skills
AnalyticsBusiness InsightsConcreteData ScienceMachine LearningMathematicsPhysics
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 5+ years in product analytics growth analytics or data science with ownership of analytics domains
- Strong quantitative foundation through degree or equivalent experience solving complex quantitative problems
- Deep proficiency in SQL and Python
- Hands-on experience with statistical modelling such as regression classification or time-to-event analysis
- Experience running rigorous experimentation and defining high-quality experiment standards
- Familiarity with LTV churn retention or conversion modelling and turning predictions into interventions
- Ability to communicate technical findings clearly to stakeholders including senior leadership
- Comfort making recommendations with imperfect signals in fast-moving low-process environments
Nice to have
- Subscription products
- Consumer products
- Marketing measurement
- Mobile data environments
Day to day
- Analyse the acquisition funnel from ad spend through quiz signup and activation to identify leakage points and compounding growth opportunities.
- Design and interpret rigorous experiments across product and growth surfaces using methods such as sequential testing CUPED and uplift analysis.
- Build and evolve metrics and lightweight predictive or causal models that improve retention conversion and LTV while guiding strategy and stakeholder decisions.
- Partner closely with Product Managers Growth Marketers Designers Engineers and leadership to translate complex findings into clear actionable recommendations.
Hiring process
- Intro chat with Talent Team
- Hiring Manager Interview
- Remote Loop
- Offer, equity and benefits breakdown