Lead - Business Analytics

Location:

Santa Clara, CA

We are seeking a Business Analytics Lead
- Commercial, Manufacturing & Supply Chain Analytics for the newly formed Data & Analytics unit on the US West Coast. This senior, onsite role leads the commercial, manufacturing and supply chain Business Analytics with AI/ML capability, combining domain-led consulting with hands-on solution leadership. The lead will engage customer operations and technology leaders to prioritize high-value AI/ML use cases, architect solutions and take them from PoC through pilot to production with offshore engineering, data science and CoE teams.

• Lead the commercial, manufacturing and supply chain AI/ML capability for the Data & Analytics unit, combining domain-led consulting with hands-on solution leadership.
• Engage manufacturing, operations, planning, logistics, procurement and technology leaders to identify problems, assess data readiness and prioritize high-value AI/ML use cases.
• Facilitate discovery and design workshops, define target architectures and convert opportunities into a practical roadmap with measurable operational outcomes.
• Architect solutions for predictive maintenance, quality, yield, forecasting, inventory, production planning, logistics and supply-risk analytics based on customer priorities.
• Guide data preparation, feature engineering, model development, validation, deployment, monitoring and continuous improvement.
• Ensure solutions integrate securely with enterprise, manufacturing and supply chain platforms and operate reliably within production workflows.
• Own or contribute to proactive proposals, RFP/RFI responses, estimates, delivery models, demonstrations and executive presentations.
• Lead PoCs and pilots through production, incorporating MLOps, explainability, responsible AI, monitoring, cost control and governance.
• Coordinate planning, staffing, technical reviews and execution governance with offshore engineering, data science and CoE teams.
• Build reusable accelerators, reference architectures and solution assets for manufacturing and supply chain analytics.
• Mentor data scientists, ML engineers and architects, establish technical standards and support opportunity qualification with account leadership.

Education:

Bachelor's degree in Computer Science, Data Science, Industrial Engineering, Operations Research, Supply Chain, Engineering or a related discipline;
Master's or PhD desirable.

Experience:

Significant professional experience leading AI/ML and analytics solutions in manufacturing and supply chain environments, including taking initiatives from use-case discovery through production adoption.

• Strong AI/ML leadership with hands-on depth in manufacturing and supply chain analytics, from use-case discovery through production adoption.
• Advanced machine learning and data science using Python, scikit-learn, PyTorch or Tensor Flow, including feature engineering, model selection, evaluation, explainability and optimization.
• Proven delivery of manufacturing use cases such as predictive maintenance, anomaly detection, quality prediction, yield improvement, process optimization, computer vision inspection or energy optimization.
• Proven delivery of supply chain use cases such as demand forecasting, inventory optimization, supply risk sensing, production planning, logistics optimization, order fulfillment or control-tower analytics.
• Experience with time-series forecasting, optimization, simulation and machine learning techniques applied to operational data.
• Experience integrating enterprise and industrial data from ERP, MES, WMS, TMS, planning platforms, IoT, sensor, historian and streaming sources.
• Production-scale MLOps: MLflow, model serving and monitoring, feature stores, drift management, CI/CD, Docker and Kubernetes.
• Expertise in at least one cloud AI and data stack:
  Google Cloud, Azure or AWS; familiarity with Databricks and/or Snowflake is desirable.
• Understanding of modern data architecture, lakehouse patterns, Spark/PySpark, SQL, streaming, data quality, lineage and governance.
• Working knowledge of GenAI and agentic patterns for manufacturing and supply chain knowledge assistance, root-cause analysis, operational decision support and workflow automation.
• Ability to facilitate customer workshops, shape solution architectures, build business cases and communicate with operations, supply chain, engineering, data and…