Data Scientist

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 is focused on solving complex measurement challenges within a US-based client’s advertising business, rather than general data science tasks. The successful candidate will frame research questions, design rigorous studies, and develop Python code to deliver actionable insights. Daily responsibilities include measuring the impact of advertising assets on revenue, modeling click-through and ranking dynamics, and continuously evaluating ad strategies to drive data-informed decisions.

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 methods, incrementality testing, and marketing mix modeling (MMM/MTA).
- Develop models for click-through rates, ranking dynamics, and market pricing.
- Establish ongoing evaluation frameworks for advertising strategies to ensure decisions are evidence-based.
- Collaborate with engineering teams to implement research methods as production monitoring tools.
- Write production-quality Python and SQL code independently, ensuring reproducibility, version control, and peer review.
- Communicate findings clearly to non-technical stakeholders and confidently defend conclusions under scrutiny.
- Serve as the domain expert for advertising measurement within the team, guiding best practices and knowledge sharing.

Required Qualifications

- Master’s or PhD in statistics, econometrics, applied mathematics, physics, computational finance, or a related quantitative discipline.
- Minimum of five years’ experience in applied quantitative research.
- 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 ability, evidenced by publications, open-source contributions, competition participation, 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, ad-tech, or actuarial domains.
- Familiarity with time series analysis and Bayesian methods.
- Background in consulting or client-facing roles, with experience delivering research insights directly to clients.

Perks and Benefits

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

This position offers the opportunity to work on challenging measurement problems at the intersection of advertising and quantitative research, with a strong emphasis on rigorous methods and clear communication. If you are passionate about applying advanced quantitative techniques to real-world business questions and enjoy working in a collaborative environment, this role is an excellent fit.