Lead Data Scientist
Full-time
DemandTec
Role Description
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.
- 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.
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.
Requirements
- 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.
Vacancy posted 4 days ago
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