Role Overview
We are seeking an exceptional Senior Data Scientist to join our Marketing Science team, serving as both a technical leader and hands-on contributor in building advanced activation solutions that drive superior client performance. This role combines strategic leadership responsibilities with deep technical expertise in econometric modelling and predictive analytics.
What You Will Do
Develop and implement training programs to enhance team capabilities in advanced analytics and marketing analytics, lead and mentor a team of data scientists and analysts, and establish team priorities, allocate resources effectively, and ensure delivery of high-quality analytical solutions.
Why It Might Be a Fit
The successful candidate will need to demonstrate an ability to manage multiple projects simultaneously, drive technical excellence and innovation in marketing measurement, and foster a culture of continuous learning, collaboration, and excellence within the department.
Requirements
- Advanced expertise in Marketing Mix Modelling (MMM) including media saturation curves, adstock effects, and base vs. incremental decomposition
- Strong econometrics background with experience in time series analysis, panel data methods, and causal inference
- Proficiency in predictive modelling using machine learning techniques (regression, tree-based methods, neural networks)
- Programming expertise in R and/or Python with experience in relevant libraries (e.g., tidyverse, scikit-learn, PyMC3, Stan)
- Experience with cloud platforms (AWS, GCP, Azure) and big data technologies (Spark, SQL)
- Knowledge of experimental design and A/B testing methodologies
- Familiarity with marketing measurement frameworks including attribution, incrementality testing, and media optimization
Benefits
- Competitive medical insurance
- Group retirement plans
- Vision insurance
- Dental insurance
- Significant paid time off
- Preferential partner discounts
- Employee mental health awareness days
To apply for this job please visit job-boards.greenhouse.io.

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