Senior Data Scientist – Experimentation

Senior Data Scientist – Experimentation

Requirements

• MSc / Bachelors (preferred in a scientific discipline with a strong focus on experimentation and causal inference)
• Minimum of 5 years of proven experience as a data scientist, with a demonstrated track record of successfully conducting A/B tests and experiments within a dynamic tech company, preferably in an e-commerce or direct-to-consumer business setting
• Solid grasp of advanced statistical concepts (e.g., Bayesian statistics; sequential testing; multilevel and generalized linear models, double ML; timeseries; bootstrapping)
• Practical experience with causal inference and experimentation, including experiment design and platform setup.
• Expertise in Python and SQL, with direct experience working with very large datasets. Production-level modeling experience is preferred.
• Proven experience leading data-driven projects from definition to execution, influencing business decisions and outcomes.
• Practical experience in time series analyses, forecasting techniques, cohort and survival analyses.
• Strong organizational skills, a sense of ownership and accountability, and the ability to lead projects independently.
• Excellent communication skills with the ability to tailor messages to different audiences, from technical teams to executives.
• Proficiency in building compelling stories through data visualization and narratives.

Responsibilities

• Design, oversee setup, and analyze experiments to quantify the impact of marketing investments and to enhance our understanding of products.
• Use your expertise in AB testing, marketing channel lift studies, and causal inference to suggest innovative approaches to experimentation and contribute to strategic decision-making processes.
• Own the complete test design process, from sample size estimation through deployment, analysis and reporting while working hand in hand with channel managers/product owners and business strategy leaders.
• Lead the development, deployment, and adoption of causal inference models to measure marketing campaigns, optimizing investments across short and long-term business objectives.
• Take ownership of end-to-end projects, operating where there’s a high degree of ambiguity, and delivering results within ambitious timelines.
• Translate insights into relevant business recommendations, anticipating the needs of business stakeholders.
• Act as a mentor, guiding and coaching junior Data Scientists in technical and storytelling aspects.

Preferred Qualifications

• Production-level modeling experience is preferred.