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Tier-1 brand, popular Data Scientist title with broad ML/GenAI and deployment skill requirements.
ML/GenAI and deployment skills are transferable, but insurance sales analytics domain knowledge increases specificity.
Specific ML/GenAI, deployment (Lambda/ECS), and statistical programming requirements make shortlisting strict.
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Engage with business teams to understand requirements and translate them into data science solutions.
Extract, process, and validate large datasets; automate data collection and develop machine learning models using algorithms like regression, decision trees, and boosting.
Build and deploy GenAI models (e.g., chatbots, summarization) and present insights through data visualization tools.
Proficient in statistical programming languages (R, Python) and database query languages (SQL).
Experience with data visualization tools such as Tableau or QlikSense.
Knowledge of machine learning algorithms and advanced AI techniques including GenAI, neural networks, NLP, image and speech processing.
Work Experience Required: Not explicitly mentioned in the JD.
Able to translate complex business challenges into data science solutions with measurable impact.
Experience in developing and deploying AI/ML models in production environments using cloud services (e.g., Lambda, ECS).
Expertise in advanced AI techniques, including GenAI and NLP, aligned with strategic use of data visualization for business insights.