Senior Data Scientist, ML; Insurance Underwriting

Position: Senior Data Scientist, ML (Insurance Underwriting)
We are seeking an experienced individual contributor with deep expertise in developing and deploying production-ready AI/ML solutions. As a Senior Data Scientist, you will work under the guidance of a Lead Data Scientist and collaborate with cross-functional teams across Data Science, Data Engineering, and business groups. The ideal candidate has a strong technical foundation, excels in coding, pays close attention to detail, and brings a passion for analytical thinking and problem-solving.

You Will

• Lead use cases or work streams while mentoring junior data scientists
• Support end-to-end model development, including data exploration, feature engineering, model training, validation, and ensuring quality, security, and fairness
• Contribute to project scoping, data design, analysis, modeling, and final presentations
• Perform data wrangling, fuzzy matching, ETL, and dataset preparation across diverse data sources
• Apply advanced statistical and AI/ML techniques to build scalable predictive models
• Conduct data quality checks during both development and production stages
• Package and deploy models in partnership with Data Engineering and MLOps teams
• Implement new statistical or mathematical methodologies as needed
• Explore innovative approaches using data mining, visualization, and modern ML techniques
• Partner with stakeholders to identify opportunities where data can drive measurable business value
• Present findings through compelling data visualizations and clear communication
• Maintain data accuracy, conduct ongoing quality control, and troubleshoot anomalies
• Adhere to model governance, documentation, and testing best practices
• Stay current on industry trends by participating in relevant conferences and professional communities
• Contribute to the standardization of tools, processes, and best practices within the Data Science team
• Build LLM and AI-powered prototypes with lightweight UI frameworks (such as Streamlit) to support adoption and user testing

You Are

• Passionate about emerging technology and excited to apply new AI/ML advancements
• Analytical, curious, and experienced in developing data-driven solutions to complex business challenges
• Energized by deploying real-world AI/ML models that produce measurable value
• Collaborative and comfortable working alongside data engineers, product teams, and cross-functional partners

You Have

• PhD with 2+ years of experience or Master's degree with 4+ years of experience in Statistics, Computer Science, Engineering, Applied Mathematics, or a related field
• Experience in insurance underwriting (strongly preferred)
• 3+ years of hands-on machine learning development experience
• Strong understanding of statistical modeling and applied analytics
• Experience with a range of ML techniques (clustering, decision trees, boosting, neural networks, etc.) and knowledge of their strengths and limitations
• Demonstrated experience with experimental design and execution
• Hands-on experience with data wrangling, fuzzy matching, regular expressions, distributed computing, and parallelization
• Advanced programming skills in Python
• Solid foundation in algorithms and machine learning model development
• Excellent communication skills and the ability to explain complex concepts clearly
• Ability to collaborate across Product, Engineering, and business stakeholders at both technical and strategic levels
• Strong analytical and problem-solving abilities with exceptional attention to detail
• Proven experience providing technical leadership or mentoring to other data scientists
• Strong project management skills, including performance tracking and delivery at scale
• Experience communicating impact, tradeoffs, and recommendations to non-technical audiences
• Working knowledge of software engineering best practices (Git/Git Hub, testing, logging)
• Familiarity with NLP, LLMs, RAG architectures, agent frameworks, and safe automation practices
• Experience in insurance, financial services, or similar domains is a plus