Note: The job is a remote job and is open to candidates in USA. DemandTec is a retail analytics and demand science platform that modernizes pricing and promotional decisions using AI-powered intelligence. They are hiring a Lead Data Scientist to own the technical roadmap for ML and GenAI capabilities, leading a distributed team to enhance their analytics platform.
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
Skills
- 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
- 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
Company Overview