Requirements

Key Responsibilities
• Own the technical roadmap for ML/AI models powering price optimization, demand forecasting, promotion effectiveness, and markdown recommendations.
• Architect and lead development of GenAI-powered agents and copilots (e.g., pricing copilots, demand intelligence agents) in partnership with engineering and product.
• Set technical standards for model development, validation, and MLOps across the data science organization.
• Mentor, coach, and grow a distributed team of data scientists, including direct oversight of the China and Poland-based team.
• Partner with product and engineering leadership to translate retail and trade-promotion business problems into Data Science solutions.
• Make build-vs-buy calls on LLM/GenAI tooling and vendor platforms together with ENG.
• Present model performance, technical roadmap, and AI strategy to executive leadership and, where relevant, customers and prospects.
• Track emerging AI/ML techniques and assess their applicability to retail and CPG use cases.
• Develop scalable feature engineering workflows over large retail datasets.

Required Qualifications
• 7+ years of experience in data science or applied ML, including 2+ years leading data scientists or a technical team.
• Proven track record shipping production ML models at scale.
• Experience designing, building, and shipping models for price elasticity, demand forecasting, promotion effectiveness, and similar retail/CPG use cases.
• Strong communication skills - able to translate technical work into business impact for executives and customers.

Technical Skills
• Proficiency in Python, SQL, and machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
• Familiarity with GenAI frameworks (e.g., LLMs, Dify, LangChain, RAG pipelines).
• Familiarity with cloud-based data platforms (e.g., AWS, GCP, Azure) and big data technologies (e.g., Spark, Hadoop, Databricks).
• Experience with data visualization tools (e.g., Power BI, Tableau) and modern MLOps practices.