Marketing data scientist
We are seeking a highly skilled and inquisitive Marketing Data Scientist to join our North American Marketing Data Science team. This role will be pivotal in advancing our in-house capabilities in Marketing Mix Modeling (MMM), experimentation, and multi-touch attribution (MTA). The ideal candidate will have hands-on experience with open-source MMM tools, causal inference, and A/B testing frameworks, and will be passionate about translating complex data into actionable insights that drive smarter media investment, customer engagement, and marketing optimization.
Key Responsibilities- Consults on analytical solutions to understand, analyze, and synthesize business requirements, enabling high-quality, fact-based decisions that drive better marketing outcomes and support strategic initiatives.
- Lead the development and implementation of in-house MMM solutions using open-source packages (e.g., Robyn, Meridian, LightweightMMM, PyMC).
- Designs, develops, and implements innovative analytical solutions including MMM, MTA, and causal inference frameworks.
- Design and execute robust experimentation frameworks including A/B testing, uplift modeling, and causal inference to evaluate marketing effectiveness.
- Provides expert guidance on the configuration, functionality, and usability of data management, analytics, and visualization technologies.
- Supports the development of strategy and roadmap for data quality, modeling, reporting, and advanced decision support tools and develop scalable, reproducible analytical pipelines for marketing analytics.
- Builds and maintains effective relationships with internal and external stakeholders to align analytics with business goals.
- Structures and assembles multi-dimensional data sets across various granularities (e.g., customer, product, transaction, media).
- Integrates data from multiple sources to enhance analysis, streamline reporting, and improve marketing performance measurement.
- Documents and maintains operational procedures related to analytical and reporting processes.
- Typically, 4–6 years of experience in marketing analytics, data science, or econometrics, with a post-secondary degree in a quantitative field (e.g., Statistics, Economics, Data Science, Computer Science, Marketing Analytics).
- Strong hands-on experience with open-source MMM tools (e.g., Robyn, LightweightMMM, PyMC, Prophet).
- Proficiency in Python and SQL; familiarity with R is a plus.
- Solid understanding of MTA, attribution modeling, causal inference, design of experimentation
- Experience with cloud-based data platforms (e.g., AWS, GCP, DataIku).
- Skilled in data visualization tools (e.g., PowerBI, Looker, Tableau).
- Strong analytical and problem-solving skills with a data-driven mindset.
- Excellent communication skills with the ability to influence and collaborate across teams.
- Ability to work independently on complex analytical tasks and deliver high-impact insights.
- Familiarity with traditional and digital media data sources (e.g., Kantar, Nielsen, Google Ads, Meta).
- Experience building custom MMM models from scratch and validating them through experimentation.
- Knowledge of Bayesian modeling and probabilistic programming.
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