Senior Data Scientist - Consumer
Inactive
US remote-friendlyFull-TimeSenior
Salary190800 - 267100 USD per year
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Job Details
- Experience
- For M.S. holders: 5+ years; For Ph.D. holders: 4+ years
- Required Skills
- PythonSQLA/B testingR
Requirements
- Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
- For M.S. holders: 5+ years of industry experience in applied science or data science roles
- For Ph.D. holders: 4+ years of industry experience in applied science or data science roles
- Expertise in querying relational databases (SQL)
- Expertise in programming languages (e.g., R / Python)
- Deep understanding of online experimentation (A/B testing)
- Deep understanding of causal inference
- Deep understanding of statistical techniques
- Comfortable in innovative and fast-paced environments
- Bias toward action
- Strong technical communication / data storytelling skills
- Demonstrated ability to discuss complex topics with technical and non-technical audiences alike
- Able to tackle ambiguous and undefined problems by creating an action plan, getting feedback, and iterating
Responsibilities
- Develop action-oriented insights to drive the product strategy through observational causal analysis and experiment meta-analysis
- Clearly communicate results to stakeholders up to the C-suite to take action based on recommendations
- Uplevel experimentation practices on the team through guiding design, execution, and deep dive analyses to maximize learnings from A/B tests
- Create new ETLs, tables, dashboards, and other self-serve tools to enable other data scientists and cross-functional partners to find and interact with data seamlessly
- Design, evaluate, and/or measure team-level KPIs to enable quarterly goal setting and demonstrate team impact
- Regularly engage with stakeholders to gather feedback and share progress on work at all stages to ensure alignment between DS and other teams on business goals and outcomes
- Mentor more junior data scientists and business partners in data science best practices and methods to increase data literacy and improve decision making
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