Intuit's Accountant Data Science team is seeking an experienced Data Scientist to leverage data for smarter decisions and measurable business outcomes by influencing strategy through rigorous experimentation, advanced statistical analysis, and predictive modeling.
Requirements
- Deep expertise in experimental design (A/B testing, multivariate tests) and causal inference methods (e.g., propensity scoring, synthetic controls, difference-in-differences).
- Strong proficiency in SQL and Python or R for data extraction, wrangling, analysis, and modeling.
- Demonstrated ability to tell stories with data, including building clear visualizations and delivering insights that drive decisions at the executive level.
- Proven experience working with large-scale datasets and modern data platforms (e.g., BigQuery, Snowflake, Databricks).
Responsibilities
- Designing rigorous experiments
- Shaping data pipelines
- Performing advanced statistical analyses
- Developing predictive models
- Communicating insights that influence strategy
- Design, implement, and analyze A/B tests and other experiments to evaluate new product features, marketing strategies, and customer engagement initiatives.
- Apply causal inference methods to assess the true impact of product and marketing interventions.
Other
- Conceptualizing business opportunities, formulating hypotheses, defining goals and key metrics, and delivering actionable recommendations.
- Translate complex analyses into compelling stories that influence executive decision-making.
- Partner with stakeholders across Product, Design, Marketing, and Engineering to shape data-driven strategies.
- Advanced degree in Data Science, Statistics, Economics, Computer Science, or a related quantitative field.
- 5+ years of experience in applied data science or analytics, with a strong track record in product and marketing contexts.
