Senior MMM Data Scientist

O projekcie: We are a team of tech and data enthusiasts on a mission to bring together the best minds in IT and analytics. Our goal is to build cutting-edge analytical hubs that empower our partners to become truly data-driven organizations. Join one of the largest in-house MMM (Marketing Mix Modeling) teams in the industry, building next-generation analytics solutions at worldwide scale. As part of a flagship initiative within a leading organization operating in over 190 markets, our team is at the forefront of data-driven transformation and has strong visibility across the business. We are looking for a Senior Data Scientist with MMM expertise to help shape, develop, and deploy impactful analytical solutions as part of the Global Analytics Unit—a central, high-priority function driving innovation across the company. In this high-impact role, you will own the full data science lifecycle: from exploratory analysis and model development to refactoring, testing, deployment, and performance optimization. You will work alongside talented MMM professionals and make a truly global impact with your work. If you want to contribute to meaningful, large-scale projects and help our partners make smarter, data-driven decisions—this role is for you. Why join us If you’re looking for an opportunity to: - Tackle complex, real-world business challenges using advanced analytics and machine learning. - Build and deploy production-grade models that influence decisions across global markets. - Work in one of the largest and most skilled MMM teams in the industry. - Join a product-oriented FMCG environment that values innovation and technical excellence. - Use the latest GenAI tools, including GitHub Copilot, to make your work more efficient …this role might be the perfect fit. You will also benefit from: - Flexible working hours with a hybrid/remote work model. - Private medical care and a Multisport card. - Access to online learning platforms, certifications, and global knowledge exchange. - A relaxed, non-corporate atmosphere with strong respect for expertise and ownership. - A modern office in central Warsaw with excellent transport links. Wymagania: Requirements - 5+ years of professional experience in Data Science or ML Engineering, including production deployments. - At least 1 year of experience developing Marketing Mix Models (MMM) or working with Time Series Analysis. - MSc or PhD in Computer Science, Statistics, Mathematics, Physics, or a related field. - Strong Python skills and solid software engineering foundations (OOP, modular design, testing). - Strong experience with ML frameworks and the NumFOCUS ecosystem: pandas, scikit-learn, SciPy, NumPy, Matplotlib. - Familiarity with cloud computing (Azure experience is a plus). - Experience designing robust validation and monitoring strategies for production ML models. - Strong analytical mindset and the ability to think critically about model behavior. - Fluency in English (spoken and written), as you will collaborate globally. Nice to have - Experience with Google Meridian, LightweightMMM, or Robyn. - Experience with Bayesian modeling. - Knowledge of MCMC methods. - Understanding of CI/CD and MLOps pipelines, Docker/Kubernetes, and model deployment practices. - Experience working in agile, cross-functional environments. - Exposure to multi-tenant or global-scale data systems. - Publications, GitHub portfolio, or open-source contributions. Codzienne zadania: - Lead end-to-end MMM data science projects—from problem framing and data exploration to deployment and ongoing monitoring. - Develop, refactor, and productionize robust data preprocessing pipelines to ensure stability and scalability. - Design and integrate new features into our advanced MMM framework to improve performance and analytical capabilities. - Build and maintain reusable helper functions for hyperparameter optimization, feature selection, and model evaluation. - Improve model accuracy and diagnostics using weighted R², adjusted R², Xi correlation, RMSE, and MAE. - Automate baseline validation and implement standardized approaches for benchmarking model performance. - Work closely with Data Engineers and MLOps Specialists to deploy models into production within Azure-based infrastructure. - Collaborate with business stakeholders to translate analytical insights into clear, actionable recommendations.