Senior Data Scientist - Supply Chain

We are building an AI-enabled supply chain that senses, predicts, prescribes, and acts. As a Senior Data Scientist, you will architect and deliver advanced analytical solutions that shape how the Supply Chain organization makes decisions. You will lead the development of predictive, prescriptive, optimization, anomaly detection, and simulation models - and ensure they are embedded into real workflows, systems, and AI agents.

This role is ideal for someone who can operate at both the strategic and technical levels: designing decision frameworks, influencing cross-functional partners, and building models that materially improve cost, service, and resilience.

Responsibilities include but not limited to:

Lead the design and development of predictive, prescriptive, and simulation models that support enterprise-level supply chain decisions
Architect optimization frameworks that balance cost, service, capacity, and risk under real-world constraints
Translate ambiguous business problems into structured analytical approaches and decision models
Identify and quantify systemic risks, variability, and anomalies across supply chain operations
Build scenario and simulation environments that enable leadership to evaluate strategic tradeoffs and “what-if” conditions
Partner with senior stakeholders to define requirements and influence decision‑making
Ensure analytical outputs are integrated into AI agents, planning systems, and operational workflows
Mentor other data scientists and elevate analytical standards across the team
Drive best practices in data quality, feature engineering, model governance, and performance monitoring
Requirements:

Basic Qualifications:

Master's degree in data science, statistics, computer science or related field
8+ years of professional experience, including 5+ years in supply chain analytics, optimization, or simulation
Proven ability to operate independently, lead analytical workstreams end-to-end, and influence decisions with minimal oversight
Strong proficiency in Python and SQL, with the ability to design scalable analytical pipelines
Deep experience with predictive modeling (statistical, ML, deep learning), optimization techniques (LP, MIP, constraint programming), and simulation methods (Monte Carlo, discrete event)
Strong understanding of supply chain processes and the analytical levers that influence cost, service, and resilience
Experience designing decision frameworks and translating them into optimization or prescriptive models
Familiarity with machine learning techniques (clustering, tree-based models, neural networks) and their practical tradeoffs
Experience with data manipulation libraries (pandas, NumPy) and ML frameworks (scikit-learn, XGBoost, PyTorch, TensorFlow)
Experience with big data platforms such as Spark, Databricks, or Snowflake
Ability to communicate complex analytical concepts to senior leaders in clear, business-focused language
Experience mentoring or leading technical contributors is a plus

Preferred Qualifications:

PhD
Experience designing optimization or simulation models for supply chain decisions
Background in stochastic modeling, network optimization, or discrete-event simulation
Experience embedding predictive or prescriptive models into operational systems
Strong executive communication skills and experience influencing senior stakeholders