Senior Machine Learning Engineer – Marketing ROI Modeling (PhD in AI / Econometr

Key Responsibilities:

• Design, develop, and maintain machine learning and econometric models to measure and forecast marketing channel ROI.
• Implement and fine-tune Kalman filters, Bayesian hierarchical models, and state-space models to track and predict marketing performance.
• Integrate macroeconomic and market-level factors to enhance model robustness and business relevance.
• Work with large-scale marketing datasets on Azure and Snowflake, leveraging Python and SQL for data wrangling, modeling, and automation.
• Collaborate with marketing, data engineering, and analytics teams to design scalable modeling pipelines.
• Optimize models for accuracy, interpretability, and efficiency on Azure infrastructure.
• Translate model outputs into actionable insights and communicate findings to marketing and business stakeholders.
• Continuously improve modeling frameworks through validation, experimentation, and parameter tuning.

Required Qualifications:

• PhD in Artificial Intelligence, Machine Learning, Econometrics, Applied Mathematics, or a related quantitative discipline.
• 6+ years of professional experience in machine learning, data science, or econometric modeling.
• Proven experience in marketing analytics, media mix modelling (MMM), or ROI analysis.
• Strong understanding and practical experience with Kalman filters, Bayesian inference, and time-series modeling.
• Advanced proficiency in Python (PyMC, scikit-learn, TensorFlow, statsmodels).
• Strong SQL skills and professional experience using Snowflake.
• Expertise in Azure-based data and ML environments (Azure ML, Azure Data Factory, Azure Synapse).
• Understanding of macroeconomic trends and their impact on consumer behavior and marketing effectiveness.
• Excellent communication and teamwork skills.

Preferred Qualifications:

• Experience with Marketing Mix Modelling (MMM), Incrementality Testing, or causal inference techniques (difference-in-differences, synthetic controls).
• Knowledge of MLOps best practices (model versioning, CI/CD, monitoring, and retraining pipelines in Azure).
• Research or applied experience with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems.
• Ability to integrate AI-driven insights from LLMs into marketing analytics and decision-support tools.
• Background in applied research within marketing science, econometrics, or consumer analytics.

What We Offer:

• The opportunity to work on high-impact AI and econometric projects with a globally recognized brand.
• Collaboration with an international, cross-functional team.
• Exposure to cutting-edge AI and marketing analytics, from advanced econometric modeling to modern LLM-based tools.
• Continuous learning and growth in both AI research and marketing data science.
• Long-term B2B collaboration.
• Comprehensive private medical insurance or budget for your medical needs.
• Paid sick leave, vacation, and public holidays.
• Continuous learning support, including unlimited certification sponsorship.