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 complex measurement challenges within a US-based client’s advertising business and is not a general data science position. The successful candidate will frame research questions, design rigorous studies, and develop Python code to deliver actionable insights. Day-to-day responsibilities include measuring the impact of advertising assets on revenue, modeling click-through and ranking dynamics, and establishing continuous evaluation frameworks for ad strategy.

Key Responsibilities

- Translate broad business questions into precise, testable research hypotheses.
- 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 advertising decisions are evidence-based rather than intuitive.
- Collaborate with engineering teams to convert research methodologies into scalable production monitors.
- Write production-quality Python and SQL code independently, ensuring reproducibility, version control, and peer review.
- Present research findings clearly to non-technical stakeholders and confidently defend conclusions under scrutiny.
- Serve as the subject matter expert for advertising measurement within the team, providing domain leadership.

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 independent research capabilities, evidenced by publications, open-source contributions, competition results, or a professional portfolio.
- Excellent communication skills, with the ability to explain complex statistical concepts to non-technical audiences.

Preferred Qualifications and Benefits

- Experience in markets, trading, pricing, advertising technology, or actuarial science.
- Familiarity with time series analysis or Bayesian statistical methods.
- Background in consulting or client-facing roles, delivering quantitative insights.
- Benefits include gym, travel, and food allowances, annual certification support, paid time off and holidays, and bi-annual performance reviews with bonuses.

This role offers an opportunity to work on challenging measurement problems at the intersection of advertising and quantitative research, contributing directly to strategic decision-making in a dynamic environment.