Data Scientist

Experteer Overview In this role you will drive time-series analytics and enterprise-scale AI in TI’s SMA group, turning sensor and process data into reliable, production-ready models. You collaborate with facilities engineers and operations teams to solve real operations problems and deploy intelligent, scalable solutions. You’ll balance simple statistical approaches with advanced methods, ensuring robust, production-grade systems. A strong focus on agentic AI and cross-functional impact anchors the role in TI’s manufacturing excellence. You will shape the data science strategy for time-series analytics and AI deployment across global facilities. Compensation / Benefits * Analyze and model complex time-series data from equipment, sensors, and processes to create production-grade models * Develop and deploy anomaly detection, predictive maintenance, and forecasting solutions at scale * Design end-to-end ML pipelines that reduce manual analysis and improve operational decision-making * Build scalable, maintainable data science solutions with clean architecture, testing, and version control * Design and deploy Agentic AI solutions using MCP and A2A to create intelligent data-analysis workflows * Apply ML engineering fundamentals to ensure models are robust and production-ready across distributed environments * Define technical strategy for time-series analytics and enterprise AI deployment * Lead enterprise-wide Agentic AI initiatives from proof of concept to scaled deployment * Mentor data scientists and engineers, sharing knowledge and elevating team capability * Identify and implement continuous improvements beyond the assigned scope Tasks * Master’s degree in Data Science, Computer Science, Mathematics, Statistics, or a related quantitative field * 5+ years of experience as a Data Scientist working with time-series data in manufacturing or facilities domains * Experience deploying enterprise-scale Agentic AI solutions * Deep proficiency in Python and SQL for data processing, feature engineering, and ML development * Hands-on time-series methods experience (anomaly detection, forecasting, signal processing; ARIMA, Prophet, LSTM, Isolation Forest, deep learning, etc.) * Experience with MLOps, including versioning, monitoring, and CI/CD for ML pipelines * Ability to translate complex operational problems into production-grade analytical solutions * Familiarity with AI-assisted development tools Key requirements * competitive pay and benefits * opportunity to influence global manufacturing * career development and leadership opportunities

with scalable, maintainable data science solutions with clean architecture, testing, and version control * Design and deploy Agentic AI solutions using MCP and A2A to create intelligent data-analysis workflows * Apply ML engineering fundamentals to ensure models are robust and production-ready across distributed environments * Define technical strategy for time-series analytics and enterprise AI deployment * Lead enterprise-wide Agentic AI initiatives from proof of concept to scaled deployment * Mentor data scientists and engineers, sharing knowledge and elevating team capability * Identify and implement continuous improvements beyond the assigned scope Tasks * Master’s degree in Data Science, Computer Science, Mathematics, Statistics, or a related quantitative field * 5+ years of experience as a Data Scientist working with time-series data in manufacturing or facilities domains * Experience deploying enterprise-scale Agentic AI solutions * Deep proficiency in Python and SQL for data aaa Science, feature engineering, and ML development * Hands-on time-series methods experience (anomaly detection, forecasting, signal processing; ARIMA, Prophet, LSTM, Isolation Forest, deep learning, etc.) * Experience with MLOps, including versioning, monitoring, and CI/CD for ML pipelines * Ability to translate complex operational problems into production-grade analytical solutions * Familiarity with AI-assisted development tools Key requirements * competitive pay and benefits * opportunity to influence global manufacturing * career development and leadership opportunities