Lead Data Scientist at DemandTec

, , United States -

Full Time

Start Date

Immediate

Expiry Date

04 Oct, 26

Salary

0.0

Posted On

06 Jul, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, SQL, Machine Learning, GenAI, LLMs, RAG Pipelines, MLOps, Demand Forecasting, Price Optimization, PyTorch, TensorFlow, Scikit-learn, Spark, Databricks, Power BI, Tableau

Industry

Software Development

Description

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. 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.

Responsibilities

Own the technical roadmap for ML and GenAI capabilities, focusing on price optimization, demand forecasting, and AI-driven copilots. Lead and mentor a distributed team of data scientists while partnering with product and engineering leadership to solve retail business problems.