Experimentation : Design, implement, and analyze experiments to measure the impact of new initiatives leveraging Bayesian Inference and CUPED.
Causal Inference : Lead causal inference and econometric analyses to understand and influence key levers of business growth with a crisp understanding of incremental impact.
Define KPIs and Success Metrics : Establish key business indicators for projects, ensuring alignment with company objectives.
Communication : Translate complex technical findings into clear, actionable insights for senior leadership, including product, finance, and marketing executives.
Native AI : Partner closely with our Central AI team to productionalize ML models that drive delightful, personalized experiences for our customers.
Leadership and Ownership : Demonstrate extreme accountability and proactively drive outcomes across teams and leads with influence, not authority.
Qualifications
A bachelor's degree in Data Science, Statistics, Economics, or a related quantitative field is required. Advanced degree preferred. Or equivalent work experience.
At least 7-10 years of progressive experience in a Data Science role.
Proven track record of excellent communication skills: clearly articulating complex concepts to both technical peers and non-technical stakeholders, fostering understanding and collaboration with every interaction.
Demonstrated expertise in causal inference—including but not limited to advanced experimentation, synthetic controls, regression discontinuity, and instrumental variables—with a track record of rigorously solving problems with these methods.
Applied experience supporting AI-driven user experiences.
A demonstrated ability to navigate through ambiguity and deliver results that significantly impact the business.
Proficiency in SQL and a statistical programming language such as Python and/or R. Experience with Tableau or Qlik required.