Lead Data Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership of the technical roadmap for ML/AI models that drive price optimization, demand forecasting, promotion effectiveness, and markdown recommendations.

• Design and lead the development of GenAI-powered agents and copilots (such as pricing copilots and demand intelligence agents) in collaboration with engineering and product teams.

• Establish technical standards for model development, validation, and MLOps throughout the data science organization.

• Mentor, coach, and develop a geographically distributed team of data scientists, with direct oversight of teams based in China and Poland.

• Collaborate with product and engineering leadership to convert retail and trade-promotion business challenges into Data Science solutions.

• Make decisions regarding build-vs-buy for LLM/GenAI tools and vendor platforms in conjunction with the engineering team.

• Present model performance metrics, technical roadmap, and AI strategy to executive leadership and, as appropriate, to customers and prospects.

• Monitor emerging AI/ML techniques and evaluate their relevance to retail and CPG applications.

• Create scalable feature engineering workflows for extensive retail datasets.

⛳️ Requirements

• Over 7 years of experience in data science or applied ML, including a minimum of 2 years in a leadership role overseeing data scientists or a technical team.

• Demonstrated success in deploying production ML models at scale.

• Experience in designing, constructing, and delivering models for price elasticity, demand forecasting, promotion effectiveness, and related retail/CPG scenarios.

• Excellent communication skills — capable of conveying the business impact of technical work to 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).

• Knowledge of 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.

🏝️ Benefits

• Comprehensive health and wellness benefits.

• Opportunities for professional development and continuous learning.

• Flexible work arrangements and a supportive work environment.

• Access to cutting-edge technologies and tools.