TurboTax is seeking to drive product innovation and personalization across the conversion funnel by leveraging advanced statistical approaches and data-driven insights.
Requirements
- Proficiency in SQL and a statistical programming language such as Python and/or R.
- Experience with Tableau or Qlik required.
- 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.
- Experience with Bayesian Inference and CUPED.
- Ability to develop predictive models and methodologies.
- Experience with ML models and productionalization.
Responsibilities
- Develop predictive models and methodologies to uncover growth opportunities and support long-term business planning.
- Design, implement, and analyze experiments to measure the impact of new initiatives leveraging Bayesian Inference and CUPED.
- Lead causal inference and econometric analyses to understand and influence key levers of business growth with a crisp understanding of incremental impact.
- Establish key business indicators for projects, ensuring alignment with company objectives.
- Partner closely with our Central AI team to productionalize ML models that drive delightful, personalized experiences for our customers.
- Apply rigorous, data-driven insights to shape the evolution and performance of TurboTax's AI native experiences.
- Lead initiatives that leverage advanced statistical approaches using behavioral data, user segmentation, experimentation (A/B testing), and other causal inference methods to uncover growth opportunities, improve key user flows, and enhance the end-to-end customer experience.
Other
- 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 ability to navigate through ambiguity and deliver results that significantly impact the business.
- Extreme accountability and proactively drive outcomes across teams and leads with influence, not authority.
