ML Data Scientist (7+ years experience)

We are seeking a Senior Data Scientist specializing in Demand Forecasting and Supply Chain Analytics to join our advanced analytics team. This role blends machine learning, forecasting, and large-scale data engineering to drive business-critical decisions across supply chain and operations.

You will work on building scalable forecasting models, leveraging modern data platforms such as Palantir, Databricks, and Snowflake, and translating data into actionable insights that improve planning accuracy and operational efficiency., Machine Learning & Forecasting

• Develop and deploy time-series forecasting models (ARIMA, Prophet, XGBoost, Deep Learning, etc.)
• Design demand forecasting solutions for supply chain, inventory, and salesplanning
• Improve forecast accuracy using feature engineering, external signals, and ML optimization techniques

Supply Chain & Business Impact

• Collaborate with supply chain, operations, and business stakeholders to alignforecasting outputs with business needs
• Analyze demand variability, seasonality, and trends to support inventory optimization and production planning
• Translate complex models into business-friendly insights and dashboards

Data Platform & Engineering

• Work with large-scale datasets using:

o Databricks (preferred) for ML pipelines and distributed processing

o Palantir for data integration, modeling, and operational analytics

o Snowflake for data warehousing and analytics

• Build and maintain data pipelines and feature stores
• Ensure data quality, governance, and scalability across systems

Model Deployment & MLOps

• Deploy models into production environments using CI/CD and MLOps practices
• Monitor model performance and continuously improve based on feedback loops
• Automate workflows for real-time or near-real-time forecasting

• Experience with:

o Databricks (Highly Preferred)

o Palantir Foundry (Preferred)

o Snowflake (Data Lake/Warehouse experience)

• Experience building end-to-end ML pipelines
• Exposure to data lake architectures and big data frameworks (Spark, Delta Lake)
• Knowledge of forecasting at scale in CPG, retail, or manufacturing industries