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Tier-1 brand, Bangalore metro, popular data scientist title, broad ML/NLP requirements drive high applicant competition.
Core ML/AI skills are transferable but insurance domain knowledge increases sensitivity to relevant industry experience.
Advanced degree plus mandatory ML model development and tooling experience creates high shortlisting strictness.
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Collaborate with global business partners to define project scope, conduct analyses, manage timelines, and deliver models automating underwriting and pricing processes.
Develop and implement machine learning and NLP models, ensuring they meet desired KPIs post-production.
Mentor junior team members and generate novel AI/ML approaches while maintaining up-to-date expertise in the field.
Advanced degree in data science, business analytics, computer science, statistics, mathematics, or economics.
Strong programming skills in Python and experience with ML libraries such as scikit-learn; familiarity with data engineering, transformation, and visualization tools (Qlik, Power BI) is a plus.
Proven experience in developing and maintaining machine learning models with knowledge of multiple ML techniques including deep learning.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in applying machine learning and NLP techniques to real-world business problems, specifically in automation of underwriting and pricing.
Capable of handling stakeholder requirements independently and mentoring junior colleagues, indicating a higher level of responsibility and domain expertise.
Comfortable working in a dynamic environment involving cross-functional teams and continuous learning of AI/ML advances.