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Tier-1 brand, metro location, mid-level generalist ML role, and broad required skillset increase competition.
Core ML skills transfer across industries, but automotive/manufacturing domain knowledge is advantageous.
Explicit 2–5 years requirement, master's preferred, and multiple mandatory ML technical skills.
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Identify and leverage business opportunities by analyzing data and applying advanced statistical and ML/AI methods across multiple domains including supply chain, sales, manufacturing, and computer vision.
Develop, deploy, and maintain customized and reusable AI/GenAI/ML/statistical models and dashboards for scalable business impact, collaborating closely with product and engineering teams.
Independently manage projects/products, providing technical directions to team members and ensuring analytic needs are well-defined and met throughout project lifecycles.
2 to 5 years of relevant work experience in data science or related fields.
Master's degree preferred in Statistics, Machine Learning, AI, Computer Science, or related areas from a reputed Indian institute.
Strong expertise in Python including data preprocessing, feature selection, cleansing, and transformation.
Experience with multiple applied ML algorithms (regression, classification, clustering, neural networks) and knowledge of GenAI methods (RAG, LangChain) explicitly required.
Experience applying ML/AI in domains such as supply chain analytics, sales recommendation systems, manufacturing analytics, or computer vision to solve real business problems.
Ability to work independently managing multiple projects, providing technical leadership, and coordinating cross-functional stakeholders.
Skills spanning end-to-end data science lifecycle including model development, API or web app development (Flask/Django), and deployment on cloud platforms (Azure/AWS) with containerization (Docker) and CI/CD.