Senior Marketing Mix Modeling Data Scientist

In Cyclad we work with top international IT companies in order to boost their potential in delivering outstanding, cutting-edge technologies that shape the world of the future. We are seeking an experienced Senior Marketing Mix Modeling (MMM) Data Scientist to join our team. You will serve as the technical architect of the measurement strategy. You won't just run models; you will build the engine that defines how we allocate multi-million dollar budgets. Leveraging Google’s Meridian framework, you will bridge the gap between complex Bayesian statistics and actionable marketing intelligence, ensuring every dollar spent is backed by rigorous data science.

Type of project: IT Services Office location: Poland Work model: Remote from PL Budget: 165 - 185 PLN net/ h - b2b Only candidates with citizenship in the European Union and residence in Poland Start date: ASAP

• Proven track record of deploying Google’s Meridian (or similar Bayesian frameworks like LightweightMMM) in a production environment
• Advanced proficiency in Python, specifically within the data stack (Pandas, NumPy, PyMC/ArviZ, and Scikit-learn)
• 6+ years of experience in econometrics or causal inference, with a deep understanding of time-series analysis and multivariate regression
• A solid grasp of the modern media landscape, including nuances in programmatic, social, search, and traditional broadcast attribution
• Very good English skills

Nice to have:

• Experience scaling workflows on Google Cloud Platform (GCP), specifically using BigQuery for data warehousing and Vertex AI for model lifecycle management
• Familiarity with CI/CD, Git workflows, and containerization (Docker) to ensure model reproducibility
• Ability to build custom dashboards (Looker, Tableau, or Streamlit) to make model results accessible to non-technical stakeholders

• Design, develop, and refine end-to-end Marketing Mix Models using the Meridian framework to quantify the incremental impact of offline and online media channels
• Build and maintain scalable Python pipelines for data ingestion, feature engineering (addressing seasonality, price elasticity, and macro-trends), and automated model validation
• Utilize Bayesian methods to incorporate prior knowledge and reach deeper insights into diminishing returns (S-curves) and media ad-stock effects
• Translate technical model outputs (ROI, mCPA, and contribution charts) into executive-level narratives that guide CMOs and media planners in budget reallocation
• Partner with the broader Data Science team to calibrate MMM results using "Ground Truth" data from incrementality tests (Geo-experiments or Lift studies)

Only candidates with citizenship in the European Union and residence in Poland