As a Lead Data Scientist (Marketing Measurement), you will leverage expertise in Statistics, Mathematics, Data Science, Artificial Intelligence, Machine Learning, and Econometrics to design, prototype, and build next-generation advanced analytics solutions. You will partner with product owners, business stakeholders, and fellow data scientists to define technical problem statements, test hypotheses, and create efficient, scalable models that drive real-world marketing and media decisions.
Key Responsibilities
- Partner with data science leadership, machine learning engineers, and business/product teams to develop advanced machine learning and optimization models using best-in-class tools and technologies.
- Provide data science leadership within the product team by delivering strategic and tactical technical roadmap recommendations.
- Develop, validate, and maintain causal measurement strategies to quantify the impact of marketing channels (including Marketing Mix Models (MMM), Difference-in-Differences, Regression Discontinuity, and Causal ML approaches).
- Conduct advanced statistical and econometric analyses to measure marketing effectiveness, forecast future impact, and optimize budget allocation strategies.
- Translate complex model insights into clear, actionable recommendations for marketing, finance, and senior leadership teams.
- Design and execute A/B testing and controlled experiments for marketing campaigns to inform strategy and measure effectiveness.
- Advise business partners on technical solutions and ensure alignment with business goals.
- Act as a senior leader within the Data Science organization—shaping technical strategy, setting best practices, and contributing to team development.
- Mentor and coach junior data scientists on both technical skills and domain knowledge.
Required Qualifications
- Master’s or Ph.D. in Statistics, Applied Mathematics, Econometrics, Computer Science, or related field.
- 7+ years of experience in Data Science, Econometrics, or Marketing Analytics.
- Proven experience in causal inference methods, marketing measurement, and statistical modeling.
- Strong programming skills in Python, R, or similar languages.
- Expertise with data manipulation tools (SQL, Spark, etc.).
- Hands-on experience with machine learning frameworks (scikit-learn, TensorFlow, PyTorch, etc.).
- Ability to communicate complex analytical concepts to non-technical stakeholders.
- Experience in consumer marketing, media optimization, or digital advertising analytics.
- Familiarity with cloud platforms (AWS, GCP, or Azure) and big data technologies.
- Demonstrated leadership experience guiding teams, projects, or technical initiatives.