Data Scientist

We are seeking a Senior Data Scientist with at least five years of applied quantitative experience and a strong background in statistics, econometrics, or computational finance. This position focuses on complex measurement challenges within a US-based client’s advertising business and is not a generalist data science role. The successful candidate will be responsible for framing research questions, designing rigorous studies, and developing Python code to deliver actionable insights. Daily tasks include measuring the impact of advertising assets on revenue, modeling click-through and ranking dynamics, and establishing continuous evaluation frameworks for ad strategies. This role requires becoming the domain expert around whom the engineering team collaborates and confidently presenting findings to senior executives.

Key Responsibilities:
- Translate broad business questions into precise, testable research inquiries.
- Design and implement studies and experiments, selecting appropriate methods based on available data.
- Quantify the contribution of individual advertising assets to revenue through attribution and incrementality analysis.
- Develop models for click-through rates, ranking dynamics, and market pricing.
- Establish ongoing evaluation processes for advertising strategies to ensure data-driven decision-making.
- Collaborate with engineering teams to integrate research methodologies into production monitoring systems.
- Write production-quality Python and SQL code independently, ensuring reproducibility, version control, and peer review.
- Communicate complex statistical results clearly to non-technical stakeholders and defend conclusions under scrutiny.
- Serve as the domain owner for advertising measurement within the team, guiding strategy and execution.

Required Qualifications:
- Master’s or PhD degree in statistics, econometrics, applied mathematics, physics, computational finance, or a related quantitative discipline.
- Minimum of five years of hands-on quantitative experience.
- 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, capable of explaining complex statistical concepts to non-technical leadership.

Preferred Qualifications and Benefits:
- Experience in markets, trading, pricing, ad-tech, or actuarial fields is advantageous.
- Familiarity with time series analysis or Bayesian methods.
- Background in consulting or client-facing roles is a plus.

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 role offers a unique opportunity to lead advanced measurement initiatives in a dynamic advertising environment, working closely with engineering and executive teams to drive evidence-based strategies.