About the role
This person will embed with one or more product development teams, working collaboratively and cross-functionally to increase the impact of product iteration and experimentation. The ideal candidate combines deep technical fluency in data science and machine learning with exceptional communication skills and an acute product sense. They can identify the right questions to ask, use data analysis to create clarity in decision making, and deliver scalable data products and models as the situation demands.
Responsibilities
- Embed within one or more product development teams, building strong stakeholder connections and delivering data products and analyses that move team outcomes.
- Collaborate across functional boundaries with Product Management, Engineering, Design, Marketing, and Finance across every phase of product development.
- Own the prioritization and ROI assessment of Data Science opportunities within your area.
- Translate complex findings into clear narratives for leadership and cross-functional partners. Influence strategic decisions through technical depth and effective communication.
- Contribute to the analytical foundations within Growth, developing definitions, methodological guidelines, and self-serve dashboards that enable others to operate with data fluency.
- Mentor and learn from other Data Scientists both within the Growth pillar and across the company.
Requirements
- Experience working as a Data Scientist embedded with or supporting a product development team. You have experience creating value from data in messy real-world settings.
- Exceptional communication skills, both written and verbal, with the ability to distill complex quantitative work into crisp, actionable insights for diverse audiences.
- A graduate degree in Data Science, Statistics, Economics, or a related quantitative field, or equivalent demonstrated expertise in formal analysis methodology.
- Strong command of SQL, Python or R, AI tools, and data/analytics engineering ecosystems.
- Fluency with standard machine learning and predictive modeling techniques.
Conditions
- The offered salary is dependent upon several factors, including work experience, skills, and internal peer comparisons. The posted range is subject to change in the future. For this role, base salary is supplemented by equity compensation.