Data Scientist (Statistical Research), Marketing Insights and Analytics

- Ensure methodological rigor in vendor-led research, reviewing experimental design, statistical approaches, and validity of findings.
- Expand marketing data science capabilities, including:
- Incrementality Measurement: Develop and refine methodologies to assess marketing impact beyond standard A/B testing.
- Budget Optimization: Leverage MMM and experiment-based insights to inform media investment and marketing spend efficiency.
- Forecasting & Market Dynamics: Build predictive models for scenario planning and strategic marketing investment decisions.
- Influence cross-functional stakeholders (marketing, insights, product, engineering), driving alignment on data-driven marketing strategy.
- Advance causal inference methodologies in marketing measurement, including behavior and conversion lift studies (A/B testing with CUPED & DiD). Conduct meta-analyses to assess holistic A/B testing impact and drive strategic recommendations.
- Enhance automation & reporting, maintaining data pipelines, dashboards, and self-serve tools to streamline marketing analytics.

Qualifications

Minimum Qualifications
- Master's degree in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, Economics, or a related field.
- 5+ years in data science roles within business strategy, marketing, finance, engineering, or analytics organizations.
- Strong programming skills in SQL and either Python or R, with experience in data querying, manipulation, and advanced statistical analysis.
- Experience with experimental design methodologies, including A/B testing and causal inference techniques.
- Proven ability to effectively communicate complex data insights to both technical and non-technical audiences.
- Demonstrated ability to lead complex projects, manage stakeholder relationships, and influence decision-making processes without formal authority.

Preferred Qualifications
- Ph.D. in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, Economics, or a related field.
- Strong background in Marketing Mix Modeling (MMM), causal inference (e.g., DiD, Synthetic Control, Instrumental Variables), and experimental design beyond standard A/B testing (e.g., CUPED, meta-analysis, Bayesian methods).
- Experience designing and analyzing geo-testing, creative testing, and incrementality experiments to measure marketing effectiveness and inform budget allocation.
- Proven ability to work with marketing, product, engineering, and operations teams, translating complex statistical insights into actionable business strategies.

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $165000 - $205000 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

For Los Angeles County (unincorporated) Candidates:

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;

2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and

3. Exercising sound judgment.