Data Scientist - Research

We are seeking a Senior Quantitative Researcher with over five years of applied quantitative experience and a strong background in statistics, econometrics, or computational finance. This role focuses specifically on advanced measurement challenges within a US-based client’s advertising business and is not a general data science position. The successful candidate will frame complex business questions, design rigorous studies, and develop Python code to deliver actionable insights. Daily responsibilities include assessing how advertising assets drive revenue, modeling click-through and ranking dynamics, and establishing continuous evaluation frameworks for ad strategies.

Key Responsibilities

- Translate broad business questions into precise, testable research inquiries.
- Design studies and experiments tailored to the available data and business context.
- Measure the contribution of individual advertising assets to revenue using attribution, incrementality testing, and marketing mix modeling (MMM/MTA).
- Develop models for click-through rates, ranking dynamics, and market pricing.
- Implement ongoing evaluation systems to ensure ad strategy decisions are evidence-based rather than intuitive.
- Collaborate with engineering teams to operationalize research methods into production monitoring tools.
- Write production-quality Python and SQL code independently, ensuring all analyses are reproducible, version-controlled, and reviewable.
- Present complex findings clearly to non-technical stakeholders and confidently defend conclusions under scrutiny.
- Serve as the domain expert for advertising measurement within the team, providing leadership and guidance.

Required Qualifications

- Master’s or PhD in statistics, econometrics, applied mathematics, physics, computational finance, or a related quantitative discipline.
- Minimum of five years’ experience applying quantitative methods in a professional setting.
- Proficiency in Python (including pandas, statsmodels, scikit-learn) and SQL.
- Strong expertise in experimental design and causal inference, with a clear understanding of the limitations of each method.
- Demonstrated evidence of independent research through publications, open-source contributions, competition participation, or a professional portfolio.
- Excellent communication skills with the ability to explain statistical concepts and results to non-technical leadership.

Preferred Qualifications and Benefits

- Experience in markets, trading, pricing, ad-tech, or actuarial domains.
- Familiarity with time series analysis or Bayesian statistical methods.
- Background in consulting or client-facing delivery roles is advantageous.

Perks and Benefits

- Gym membership, travel, and food allowances.
- Annual professional certification support.
- Paid time off and holidays.
- Bi-annual performance reviews accompanied by bonus opportunities.

This position offers a unique opportunity to work at the intersection of quantitative research and advertising strategy, driving measurable business impact through rigorous analysis and innovative modeling.