This job is with TE Connectivity, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

At TE, you will unleash your potential working with people from diverse backgrounds and industries to create a safer, sustainable and more connected world.

Job Overview

This role is responsible for driving advanced analytics, AI, and machine learning solutions to improve Supply Chain performance and decision-making. The individual will work as a self-starter, translating complex business challenges across planning, procurement, inventory, manufacturing, and customer fulfillment into scalable analytical solutions. They will design, develop, and deploy diagnostic, predictive, and prescriptive models, while collaborating with global cross-functional stakeholders across business, analytics, and technology teams. The role also involves rapidly building AI-powered prototypes and MVPs, leveraging Supply Chain expertise, data science, and emerging technologies to convert data into actionable insights and business value, while owning solutions end-to-end from ideation through adoption.

Roles & Responsibility:

- Analyze Supply Chain KPIs to identify trends, risks, opportunities and root causes.
- Design complex and optimized SQL solutions across large and multiple data sources.
- Build scalable datasets and analytical solutions using Databricks, SQL, Python and enterprise data platforms.
- Build end-to-end analytical applications, including data, business logic, backend/API and user interface.
- Develop rapid prototypes and MVPs for new Analytics, AI and Supply Chain ideas.
- Design and develop Machine Learning solutions for forecasting, prediction,



anomaly detection and optimization.
- Build GenAI/LLM solutions using prompt engineering, RAG, APIs and enterprise data.
- Develop prescriptive solutions that recommend actions based on business conditions and constraints.
- Translate ambiguous business problems into structured analytical and technical solutions.
- Work with complex and fragmented enterprise data from SAP/ERP and other operational systems.
- Develop executive-level insights and recommendations for business decision-making.
- Own solutions from problem definition through design, development, testing, deployment and value realization.
- Work with IT and Data Engineering teams to transition MVPs into scalable production solutions.
- Continuously evaluate emerging AI, ML and analytics technologies for Supply Chain applications.

Desired Candidate Profile:

•6-8 years of experience in Data Science, Advanced Analytics, AI/ML, Analytics Engineering or Supply Chain Analytics.
•Strong hands-on experience solving complex Supply Chain analytics problems independently.
•Experience in automotive, manufacturing or Supply Chain environments preferred.
•Experience across planning, procurement, inventory, manufacturing, customer fulfillment use cases.
•Demonstrated experience developing analytical applications, prototypes, proof-of-concepts and MVPs.




•Demonstrated experience delivering Analytics/AI solutions from business problem through production deployment.

PROFESSIONAL EXPERIENCE:

•Robust hands-on expertise in SQL, Python, Databricks, Power BI and modern AI/ML technologies.
•Strong ability to design complex SQL queries and work with large, complex and multi-source datasets.
•Hands-on experience with Databricks, Spark/PySpark, Delta Lake and Lakehouse architecture preferred.
•Strong hands-on experience developing Machine Learning and Data Science solutions using Python.
•Experience with regression, classification, clustering, forecasting, anomaly detection and optimization techniques.
•Experience with feature engineering, model training, validation, evaluation and explainability.
•Experience developing GenAI/LLM solutions using prompt engineering, RAG, APIs and structured outputs.
•Experience building data and AI applications using Python-based application frameworks.
•Experience developing and integrating REST APIs, backend logic and database connections.
•Understanding of AI/ML deployment, monitoring, MLOps and productionization concepts.
•Robust understanding of end-to-end Supply Chain processes, constraints and performance drivers.
•Ability to translate Supply Chain processes into analytical, statistical and optimization logic.
•Experience with demand, supply, inventory, safety stock, MOQ, lead time, BOM and service-level analytics.
•Experience integrating data from SAP/ERP, CRM, WMS/TMS and other enterprise systems.
•Strong understanding of data quality, governance, security, reconciliation and lineage.<

📌 SR BUSINESS INTELLIGENCE ANALYST (Bengaluru)
🏢 TE Connectivity
📍 Bengaluru