Lead Data Scientist

DemandTec is a retail analytics and demand science platform used by grocery retailers and CPG suppliers to run pricing, promotions, markdowns, and trade fund decisions on connected, AI-powered intelligence rather than siloed point solutions. Backed by Longshore Capital, we're modernizing a market-leading core into an AI/ML-native, composable platform — with a live network of 7,800+ connected CPG suppliers, the largest and hardest-to-replicate asset in the category.

We're building the next generation of our solution platform for retail and analytics: GenAI-powered agents, real-time decisioning, and connected optimization across pricing, promotions, markdowns, and trade funds. This team sits at the center of that build.

We're hiring a Lead Data Scientist to own the technical roadmap for the ML and GenAI capabilities powering our next-generation retail and analytics platform — from price optimization and demand forecasting to promotion effectiveness and AI-driven copilots. You'll set the technical bar for the data science organization and lead a distributed team, including our Poland-based data scientists.

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.