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Tier-1 brand, popular data scientist title, mid-level experience, metro location and broad skills increase competition.
Core ML/AI skills are transferable across industries, though domain experience (automotive/supply chain) moderately matters.
Explicit 2–5 years, master's preference and specific ML/GenAI technical requirements make screening strict.
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Identify and develop data-driven business solutions by collaborating with multiple business units and stakeholders.
Create customized and scalable AI/ML/GenAI/statistical models aligned to specific customer and business requirements.
Lead projects independently, providing technical direction, and develop dashboards (e.g., PowerBI) for communicating algorithm results to end users.
Master's degree from a reputed Indian institute in Statistics, Machine Learning, AI, Computer Science, or related field preferred.
2 to 5 years of relevant work experience in data science or applied machine learning.
Strong expertise in Python, including data preprocessing, feature selection, cleansing, and transformation.
Experience with advanced machine learning algorithms (regression, classification, clustering, SVM, decision trees, neural networks) and statistical methods; domain knowledge in automotive/manufacturing is a plus.
Experienced in applying advanced AI/ML techniques in domains such as supply chain analytics, sales, manufacturing analytics, computer vision, or Generative AI.
Capable of independently managing analytics projects, translating insights into actionable business/product recommendations, and collaborating cross-functionally with product and engineering teams.
Familiarity with model deployment in cloud environments (Azure/AWS), API and web application development (Flask/Django), and containerization (Docker, CI/CD) is advantageous.