Business Data Scientist, Global Business Strategy and Operations

• Lead the analytics, data infrastructure, and measurement methodology of seller incentives, designing data pipelines and tooling to executing advanced statistical analysis and generating insights.
• Partner with Strategy and Operations and Finance stakeholders, who own the end-to-end processes for incentives design, to translate high-priority business problems into clear, data-driven strategies and decisions.
• Own the full data science life-cycle, using your causal inference, predictive modeling, and descriptive analytics expertise to build frameworks that solve business problems.
• Manage ambiguous problems working with datasets, using SQL, R, and Python to find creative, scalable solutions and build automated data pipelines, BI infrastructure, and dashboards from the ground up.
• Act as a data storyteller and partner, translating findings into compelling narratives and recommendations that influence and align executive leaders and teams (Strategy, Product, Engineering).

Minimum qualifications:

• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
  
• 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
  

Preferred qualifications:

• 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
• Experience in designing and implementing causal inference methods.
• Experience building and maintaining BI infrastructure, dashboards, and data pipelines.
• Proficiency in database querying (SQL).
• Excellent communication, presentation, and stakeholder management skills, with the ability to explain concepts to audiences.

• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
  
• 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.