Data Scientist

Job Description As a Data Scientist specializing in Generative AI (GenAI) at our company, you will be responsible for designing, building, and deploying advanced AI solutions across the insurance value chain. You will work at the intersection of machine learning, NLP, and large language models (LLMs) to extract insights, automate tasks, and create intelligent assistants for internal teams and policyholders. **Key Responsibilities:** - Develop and Fine-tune LLMs: Train and adapt large language models for domain-specific applications like policy summarization, claims document understanding, and automated customer responses. - Generative AI Solutions: Build solutions using text, image, and structured data to automate underwriting notes, claim justifications, and internal knowledge retrieval. - Data Engineering & Model Pipeline: Prepare, clean, and label unstructured insurance data. Assist in collecting, cleaning, and preprocessing data for analysis and modeling. - Participate in strategic decision-making related to AI directions and product architectures. - Prompt Engineering: Design, optimize, and evaluate prompts for LLM-based tools to ensure accuracy and consistency in outputs. - Integration with Business Systems: Deploy AI models into production environments integrated with CRM, claims management, and policy administration systems. - Responsible AI and Governance: Ensure fairness, transparency, and compliance with data privacy and insurance regulations when using GenAI models. - Cross-functional Collaboration: Work closely with various teams to identify automation and augmentation opportunities. - Innovation and Research: Stay updated on emerging GenAI technologies and pilot them within business contexts. **Required Qualifications:** - Masters or bachelors degree in computer science, Data Science, Statistics, AI, or related field. - 25 years of experience in data science, NLP, or AI roles with hands-on experience in GenAI / LLM-based solutions. - Strong programming experience in Python and frameworks like PyTorch, TensorFlow, Hugging Face, etc. - Proficiency in SQL, data wrangling, and cloud environments such as AWS, Azure, or GCP. - Strong grounding in machine learning, transformer architectures, and vector database technologies. - Demonstrated experience in document understanding, summarization, Q&A, or conversational AI projects. **Preferred / Nice-to-Have:** - Domain expertise in insurance, health tech, or financial services. - Experience deploying AI applications in secure, regulated environments. - Familiarity with RAG pipelines, LLMOps, or model evaluation frameworks. - Understanding of OCR, knowledge graphs, and semantic search. - Publications, hackathon wins, or open-source GenAI project contributions. **Key Metrics of Success:** - Accuracy, efficiency, and ROI of deployed GenAI models. - Reduction in manual effort for underwriting/claims/customer service teams. - Adoption and satisfaction levels of AI tools among internal users. - Compliance and governance adherence in GenAI outputs. As a Data Scientist specializing in Generative AI (GenAI) at our company, you will be responsible for designing, building, and deploying advanced AI solutions across the insurance value chain. You will work at the intersection of machine learning, NLP, and large language models (LLMs) to extract insights, automate tasks, and create intelligent assistants for internal teams and policyholders. **Key Responsibilities:** - Develop and Fine-tune LLMs: Train and adapt large language models for domain-specific applications like policy summarization, claims document understanding, and automated customer responses. - Generative AI Solutions: Build solutions using text, image, and structured data to automate underwriting notes, claim justifications, and internal knowledge retrieval. - Data Engineering & Model Pipeline: Prepare, clean, and label unstructured insurance data. Assist in collecting, cleaning, and preprocessing data for analysis and modeling. - Participate in strategic decision-making related to AI directions and product architectures. - Prompt Engineering: Design, optimize, and evaluate prompts for LLM-based tools to ensure accuracy and consistency in outputs. - Integration with Business Systems: Deploy AI models into production environments integrated with CRM, claims management, and policy administration systems. - Responsible AI and Governance: Ensure fairness, transparency, and compliance with data privacy and insurance regulations when using GenAI models. - Cross-functional Collaboration: Work closely with various teams to identify automation and augmentation opportunities. - Innovation and Research: Stay updated on emerging GenAI technologies and pilot them within business contexts. **Required Qualifications:** - Masters or bachelors degree in computer science, Data Science, Statistics, AI, or related field. - 25 years of experience in data science, NLP, or AI roles with hands-on experience in GenAI / L