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Tier-1 brand, generalist Data Scientist title, and Bangalore metro drive high applicant competition.
Core ML/NLP skills are transferable across industries but insurance domain adds moderate specificity.
Advanced degree requirement plus strong ML experience and specific tooling increases shortlisting strictness to high.
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Collaborate with global business partners to define project scope, deliver analyses, present results, and implement machine learning models.
Develop and maintain NLP, machine learning, and deep learning models to automate underwriting and pricing processes, ensuring models meet production KPIs.
Mentor junior team members and stay updated on AI/ML advancements to innovate and address business problems effectively.
Advanced degree in data science, business analytics, computer science, statistics, mathematics, or economics.
Strong programming skills in Python including experience with libraries such as Numpy, Scipy, Pandas, Regex, Matplotlib, scikit-learn, and others.
Experience in developing and maintaining machine learning models using tools like scikit-learn, H2O, R, MLlib.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in handling end-to-end machine learning projects with a focus on insurance domain use cases like underwriting and pricing automation.
Able to independently manage stakeholder requests and complex analytics projects with minimal supervision.
Strong analytical mindset with capability to research and apply novel AI/ML methods in a global, dynamic business environment.