Data Scientist
DemandTec seeks a data scientist to develop machine learning and GenAI features for its retail analytics platform, focusing on pricing, promotions, markdowns, and trade fund optimization. The role involves collaborating with the lead data scientist and a distributed team to build, ship, and maintain models and real‑time decisioning capabilities.
Skills required
About this role
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 Data Scientist in Poland to help build the ML and GenAI capabilities behind our next-generation retail and analytics platform. You'll work closely with the Lead Data Scientist and a distributed team to build models, ship GenAI features, and turn retail/CPG data into decisions that matter to our customers.
Requirements
Key Responsibilities
• Build and validate ML models supporting pricing, promotion, and markdown optimization.
• Contribute to GenAI initiatives — Build vertical-domain agents and agent clusters.
• Partner with Data Engineering to build robust, production-grade data pipelines.
• Perform exploratory data analysis and translate retail/CPG data into actionable insights.
• Build dashboards and visualizations to communicate findings to product and business stakeholders.
• Participate in code review, model validation, and documentation practices.
• Develop scalable feature engineering workflows over large retail datasets.
Required Qualifications
• 3+ years of experience in data science or applied ML roles.
• Experience designing, building, and shipping models for price optimization, demand forecasting, promotion optimization, and similar retail/CPG use cases.
• Strong analytical and problem-solving skills; comfortable working with imperfect, real-world retail data.
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.
• Hands-on experience with modern data tooling (e.g., dbt, Airflow, or similar orchestrators) and columnar/analytical engines.
Similar open roles
