Job
Description
Main Responsibilities are: Understand, Define and Articulate the art of possible of AI/ML/MLOps solutions to Business heads. Hands-on in Designing, Development and Production roll-out of AI / ML/ MLOps solutions using data science framework and methodologies (CRISP-DM and TDSP) for complex problems. Must have thorough understanding and hands-on experience of using Statistical Modeling, Classical ML, Bigdata Analytics, Deep Neural Networks, Edge AI, MLOps, Generative AI •. Should have good understanding of functional domain with data, data pipelines, data storage, data lineage and quality data management. Data Analysis and Insights Generation - Perform exploratory data analysis (EDA) on large datasets from manufacturing processes, supply chain, and other verticals to uncover trends, anomalies, and actionable insights. Identify key performance indicators (KPIs) and metrics to monitor operational efficiency, sustainability goals, and process improvements. Write efficient, reusable, and well-documented code in Python for data processing, analysis, and automation of workflows. Leverage the AWS ecosystem (e.g., S3, Redshift, Lambda, Glue) for data storage, processing, and integration. Utilize statistical and machine learning techniques to solve business problems. Collaborate with data scientists, engineers, and plant managers to translate business needs into technical solutions. Coordinate with vendors to integrate third-party tools or datasets as required. Work on strategic innovative data science projects (Generative AI/ Video Analytics/ Prescriptive Analytics/ Diagnostic Analytics/ Bigdata Analytics/ Time series Analytics etc.) with transformative vision. Work with Business Head and CFT to understand their requirements, help them understand the Art of possible, and develop innovative AI solutions. Also provide mentorship and guidance to junior Data analysts and Data Science Interns in architecting solutions and developing them.
