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
You Will
- Lead use cases or workstreams 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
- 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
- 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/GitHub, 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
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