What you’ll do

• Product recommendations. Clearly communicate recommendations to product and engineering leadership on how we can evolve our internal strategy to address shortcomings observed through deep analysis.

• Develop measurement frameworks and metrics to enable product teams to iterate efficiently and confidently, connecting short-term changes in user behavior to long-term engagement outcomes that drive top-line business metrics.

• Opportunity sizing and analysis. Write clear, actionable analyses that help teams identify areas of improvement to our growth strategies.

• Improve machine learning models which power new user recommendations and user education and marketing delivery systems, via direct contributions, new features/signals, and/or compelling analyses.

• Leadership: Lead and mentor the scope of work for at least 2 other data scientists, demonstrating high-quality output of both yourself and others for whom you are responsible. Provide continuous and candid feedback, recognizing individual strengths and contributions and flagging opportunities to improve performance.

What we’re looking for

• 8+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems on web-scale data

• Proven ability to apply scientific methods to solve real-world problems on web-scale data

• Expertise in at least one scripting language (ideally Python/R)

• Proficiency in SQL/Hive

• Strong business and product sense: delight in shaping vague questions into well-defined analyses and success metrics that drive business decisions.

• Excellent communication skills: able to lead initiatives across multiple product areas and communicate findings with leadership and product teams through compelling data narratives. 

• Experience working closely with cross-functional teams, iterating on a user product via A/B experimentation. 

• Experience leading key technical projects and substantially influencing the scope and output of others

What skills are ideal but not required?

Exposure to one or more of the following areas is beneficial. Ideal candidates would have exposure to 2+ of these areas and deep familiarity in 1 or more areas.

• Experience working in Growth function, in particular, experience working on user activation and new user onboarding experience.

• Experience with recommender systems.

• Statistical rigor. Experience with causal inference projects.

• Experience working with user research to complement learnings from data science methods.  

This position is not eligible for relocation assistance.

#LI-NM4 or #LI-REMOTE