Lead - Business Analytics

Tata Consultancy Services; Santa Clara (CA); On-site; USD 161,000 - 220,000; Full time

Job summary

Tata Consultancy Services Limited, Santa Clara, CA, seeks a senior Lead - Business Analytics for Commercial, Manufacturing & Supply Chain Analytics. You will drive AI/ML-enabled analytics across business functions, steering engagements from discovery to production in close collaboration with offshore teams.

You will shape solutions, mentor data scientists and engineers, and partner with operations and executive sponsors to deliver measurable outcomes and scalable reference architectures in a

Qualifications

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

Responsibilities

• Lead the AI/ML capability for commercial, manufacturing and supply chain analytics.
• 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-chain 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.

Skills

AI/ML leadership

Python

scikit-learn

PyTorch

TensorFlow

Time-series forecasting

MLOps

Data architecture

Spark

PySpark

SQL

Cloud platforms

Google Cloud

Azure

AWS

Databricks

Snowflake

CI/CD

MLflow

Model serving

Docker

Kubernetes

Time-series

Education

Bachelor's degree in CS/DS/Engineering/related field

Tools

Docker

Kubernetes

MLflow

Databricks

Snowflake

Spark

PySpark

Job description

Lead - Business Analytics - Commercial, Manufacturing & Supply Chain 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.

Key Responsibilities

• 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.

Qualifications

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.

Must-Have Technical / Functional Skills

• 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 TensorFlow, 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 executive stakeholders.
• Experience leading distributed onsite-offshore teams and taking AI/ML initiatives from PoC through pilot to production.

Generic Managerial Skills

• Ability to lead a specialized AI/ML capability across accounts and teams without relying solely on formal authority.
• Strong consultative communication with plant, operations, supply chain, engineering, technology and executive stakeholders.
• Ability to translate business and operational challenges into scalable analytics and AI solutions with clear value measures.
• Experience coordinating distributed onsite-offshore teams, mentoring technical talent and governing delivery quality.
• Self-directed, pragmatic and comfortable building a new capability in an evolving unit; willing to travel to customer locations as required

Salary Range: $160,700 - $220,000

Desired Candidate Profile

Qualifications

BACHELOR OF COMPUTER SCIENCE