Director, Data Science
About the role
The Principal Data Scientist serves as a senior scientific leader, owning truth, rigor, and decision quality for complex business problems. This role emphasizes hypothesis-driven analysis, statistical rigor, causal reasoning, and decision science.
Responsibilities
Lead hypothesis-driven analyses to answer high-impact strategic and business questions.
Design, develop, and evaluate statistical, econometric, and machine learning models where appropriate.
Ensure models are theoretically sound, empirically validated, interpretable, and fit-for-purpose.
Review and challenge modeling approaches for bias, stability, assumptions, and misuse.
Define how success should be measured for complex analytics and AI-enabled initiatives.
Design robust evaluation frameworks including offline validation, back-testing, and live measurement.
Elevate analytics from prediction accuracy to decision quality and business impact.
Design and review experiments including A/B tests, quasi-experiments, and observational studies.
Apply causal inference techniques (e.g., uplift modeling, DiD, matched controls) to assess incrementality.
Guide best practices for power analysis, inference, and result interpretation.
Serve as a subject-matter expert on "What worked, why, and by how much?"
Qualifications
Master’s or PhD in Statistics, Economics, Mathematics, Operations Research, Computer Science, or related quantitative discipline.
10-14+ years of experience in data science, quantitative research, or advanced analytics.
Proven track record of owning complex analytical problems end-to-end (from question formulation to decision impact).
Deep expertise in statistics, probability, and experimental design.
Strong command of causal inference and incrementality measurement.
Solid grounding in forecasting, optimization, and decision science.
Demonstrated ability to assess modeling correctness, assumptions, and limitations.
Advanced proficiency in Python for analysis and modeling (NumPy, Pandas, SciPy, Statsmodels, Scikit-learn).
Strong SQL skills and experience working with large analytical datasets (e.g., Snowflake).
Hands-on proficiency with large language models and generative AI, including prompt design, retrieval-augmented generation, structured outputs, and agentic workflows.
Rigor in designing evaluations, defining task-specific metrics, and applying statistical testing to assess reliability, calibration, hallucination risk, and incremental value over non-generative approaches.
Equally proficient in hands-on code development as well as the effective use of AI-powered coding assistants, applying both to accelerate analysis while maintaining correctness, reproducibility, and scientific rigor.
Skills
Think like a scientist: hypothesis-first, evidence-driven, and principled.
Comfortable challenging senior stakeholders using data and logic.
Values clarity, elegance, and correctness over technical novelty.
Operate as a trusted expert rather than a delivery engineer.
Benefits
The base salary range for this position is $126,000-255,000 USD per year. Placement in the range will vary based on job responsibilities and scope, geographic location, candidate's relevant experience, and other factors. Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.
We offer a wide range of benefits to meet your evolving needs and help you live your best life at work and at home. These benefits include comprehensive health care coverage and emotional well-being support, market-leading retirement, generous paid time off and parental leave, charitable giving employee match program, and educational assistance including student loan repayment, tuition reimbursement, and learning resources to develop your career.