Lead Data Scientist Risk & Customer Insights - Immediate Joiner

Hiring for: An exciting InsurTech startup building an AI-native stack for the Insurance. Role: Data Scientist Risk & Customer Insights Positions: 1 Experience: 10 to 14 years Location(s): Mumbai Type: On-site / Permanent Salary: Based on the fitment Notice Period: Immediate to 15 days Key Responsibilities Data Science & Machine Learning Lead the end-to-end lifecycle of machine learning and advanced analytics initiatives. Design, develop, validate, and deploy predictive and prescriptive models for BFSI and insurance use cases. Build scalable data science solutions leveraging structured and unstructured data. Drive model monitoring, performance tracking, explainability, and governance practices. Establish best practices for experimentation, feature engineering, model evaluation, and MLOps. Fraud & Risk Analytics Design and enhance fraud detection and fraud prevention models. Build risk scoring, propensity, anomaly detection, and behavioral analytics models. Develop decisioning frameworks for underwriting, claims, collections, and customer risk assessment. Partner with business stakeholders to translate risk and fraud strategies into analytical solutions. Continuously improve model effectiveness while balancing customer experience and operational efficiency. AI & Agentic Decisioning Explore and implement AI agent architectures that assist or automate business decision-making. Build agentic workflows that combine LLMs, predictive models, rules engines, and enterprise data. Develop AI-driven copilots and decision support systems for operational teams. Evaluate emerging AI technologies and identify practical applications within insurance and BFSI workflows. Drive responsible AI adoption with a focus on explainability, governance, and compliance. Leadership & Stakeholder Management Lead and mentor a team of data scientists and machine learning engineers. Work closely with product and engineering teams to operationalize analytical solutions. Engage directly with customers and business leaders to understand challenges and define analytical roadmaps. Contribute to Client's AI and data science strategy. Drive a culture of innovation, experimentation, and continuous learning. Required Qualifications 1014 years of experience in Data Science, Machine Learning, Advanced Analytics, or related fields. Strong experience within Banking, Financial Services, Insurance, FinTech, InsurTech, or related domains. Proven experience building and deploying machine learning models in production environments. Demonstrated experience in fraud analytics, fraud detection, risk modeling, underwriting analytics, claims analytics, or related domains. Strong understanding of supervised and unsupervised learning techniques. Hands-on expertise in Python and common data science libraries (Pandas, Scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch, etc.). Experience working with SQL and large-scale data platforms. Familiarity with cloud environments and modern MLOps practices. Strong communication, customer-facing, and stakeholder management skills. Preferred Qualifications Experience within the insurance industry. Experience with GenAI, LLMs, RAG architectures, AI agents, and agentic workflows. Familiarity with decision engines, rules engines, and enterprise workflow platforms. Experience leading teams and mentoring data scientists. Exposure to model governance, explainability, and regulatory requirements within BFSI. What Success Looks Like Delivery of measurable business impact through fraud, risk, underwriting, and decisioning models. Successful deployment of AI-powered decision support systems and agentic solutions. Strong model governance, scalability, reliability, and production adoption. High-quality collaboration across product, engineering, and business teams. Development of a high-performing data science function capable of supporting rapid growth and innovation. Hiring for: An exciting InsurTech startup building an AI-native stack for the Insurance. Role: Data Scientist Risk & Customer Insights Positions: 1 Experience: 10 to 14 years Location(s): Mumbai Type: On-site / Permanent Salary: Based on the fitment Notice Period: Immediate to 15 days Key Responsibilities Data Science & Machine Learning Lead the end-to-end lifecycle of machine learning and advanced analytics initiatives. Design, develop, validate, and deploy predictive and prescriptive models for BFSI and insurance use cases. Build scalable data science solutions leveraging structured and unstructured data. Drive model monitoring, performance tracking, explainability, and governance practices. Establish best practices for experimentation, feature engineering, model evaluation, and MLOps. Fraud & Risk Analytics Design and enhance fraud detection and fraud prevention models. Build