Data Science Manager, Consumer
New
US remote-friendlyFull-TimeManager
Salary217000 - 303900 USD per year
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Job Details
- Experience
- For masters holders, 10+ years of industry experience; For PhD holders, 6+ years of industry experience
- Required Skills
- PythonSQLA/B testingR
Requirements
- Advanced degree (masters or PhD) in a quantitative field such as: statistics, mathematics, physics, economics, or operations research
- For masters holders, 10+ years of industry experience
- For PhD holders, 6+ years of industry experience
- Experience in driving product strategy and roadmaps through analytics, ideally for consumer technology products and marketplaces
- Built, led and developed high performing product analytics teams before: ideally 2+ years of leadership experience as a people manager, leading a team of 5+ data scientists
- Teams led had expertise in causal inference, A/B testing experimentation, metric definition and governance, and product strategy
- Led initiatives to enable analytics self-serve for cross-functional teams
- Excel at communicating to both technical and non-technical people
- Ability to understand nuanced complex concepts and systems, and explain them simply
- Proficient in SQL and Python/R for hands-on analysis
- Collaborative attitude and natural curiosity and strong evidence-backed product opinions
Responsibilities
- Lead a team of talented data scientists to drive and optimize user growth by uncovering insights and driving strategic initiatives.
- Collaborate closely with cross-functional partners (Product, Engineering, Design, Marketing) to build and improve the systems that continuously drive user growth.
- Drive the adoption of strategic and tactical recommendations that are based on deep and hands-on experience with Reddit products and data skills.
- Serve as a thought-partner for product managers, engineering managers and leadership, communicating and shaping the roadmap and strategy for Reddit by identifying actionable and impactful insights.
- Be proactively involved in all phases of product development, including ideation, exploratory analysis, opportunity sizing, metrics design, offline modeling, experimentation and decision-making, post-launch monitoring/measurements.
- Maintain a keen interest in the collection and quality of underlying data (experiment design and analysis, data deep dive), along with working on ETLs, reporting dashboards and data aggregations needed for business tracking and/or ML model development.
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