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Tier-1 brand, mid-level ML role in Bangalore with broad machine-learning requirements increases competition.
Core ML engineering skills are transferable, but insurance domain knowledge and Databricks requirement increase specificity.
Mandatory Databricks, 5+ years, ML frameworks and monitoring create stringent technical filters.
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Lead the end-to-end development and deployment of machine learning models, including data preprocessing, feature engineering, model selection, validation, and performance monitoring.
Collaborate with business stakeholders to translate problems into data science projects and communicate findings for decision-making.
Build and mentor a data science team, promote best practices in coding, documentation, and collaborative development using platforms like GitHub and Databricks.
5+ years of experience in data science or model development roles.
Advanced proficiency in Python and SQL, with hands-on experience on Databricks and big data platforms such as Spark or Hadoop.
Proven expertise in machine learning algorithms including GLM, Generative AI, and neural networks using frameworks like TensorFlow or PyTorch.
Work Experience Required: Minimum 5 years in data science/model development roles.
Experienced in managing the full machine learning model lifecycle with demonstrable skills in data acquisition, exploratory data analysis, feature engineering, and model monitoring.
Strong operational focus on code quality, version control (GitHub), documentation, and stakeholder communication at multiple organizational levels.
Skilled in leading and growing technical teams within complex, data-driven environments, preferably with exposure to cloud platforms and insurance industry problems.