Principal Data Scientist

We are seeking an experienced Principal Supply Chain Data Scientist with deep technical mastery in time series forecasting and predictive analytics to join our US Delivery & Solutions team. In this role, you will lead the customer implementations including the architecture, design/development, and deployment of state-of-the-art forecasting and demand sensing algorithms that drive multi-billion-dollar supply chain decisions for Fortune 500 clients.

What you27ll do for us

• Technical Leadership & Delivery: Lead the end-to-end discovery, architectural design, prototyping, testing, and deployment of enterprise-grade AI/ML models (e.g., demand sensing, stochastic modeling, inventory and revenue optimization).
• Strategic Client Partnership: Work directly with enterprise clients, solution architects, and executive stakeholders to translate complex supply chain challenges into high-value machine learning solutions.
• Team Development: Mentor and guide cross-functional teams of data scientists and analytics consultants, maintaining high coding standards, modular design, and MLOps best practices.
• AI Innovation: Leverage the latest advancements in GenAI, deep learning, time-series forecasting, and mathematical optimization to drive continuous product and client success.
• Cross-Functional Collaboration: Partner with data engineering and project management teams to integrate custom analytical models seamlessly into the o9 Enterprise Knowledge Graph platform.

What you27ll have

• Experience: 8+ years of experience in Data Science and Analytics with a proven track record as a technical lead delivering customer-facing solutions.
• Education: Master27s or Ph.D. preferred (or Bachelor27s with equivalent experience) in Operations Research, Computer Science, Statistics, Data Analytics, Engineering, or Supply Chain.
• Domain Expertise: Deep knowledge of applied machine learning in supply chain planning (e.g., demand planning, price/assortment optimization, inventory management, or network optimization).
• Technical Stack:
  • Advanced proficiency in Python and SQL.
  • Modern ML/DL frameworks (PyTorch, TensorFlow, Scikit-Learn).
  • Scaled data platforms (Databricks, Snowflake, Spark, AWS/GCP/Azure).
  • Expertise in time-series analysis, mathematical optimization, ensemble methods, and neural networks.
• Communication: Exceptional storytelling and stakeholder management skills; ability to articulate complex mathematical concepts to business executives.