Data Scientist, P&C Insurance - Remote

Summary

Upland Capital Group, Inc. is a specialty property and casualty insurer offering insurance products in select markets. The Data Scientist will support actuarial, underwriting, claims, and other organizational functions by developing, deploying, monitoring, and maintaining statistical, machine learning, and AI models across their full lifecycle.

Responsibilities

• Translate business requirements from different stakeholders into actionable data science projects
• Drive projects forward, take ownership of project deliverables, and see assigned work through to completion
• Curate modeling datasets using internal and external data sources
• Build, test, and validate statistical and machine learning models using appropriate techniques, grounded in sound statistical reasoning
• Clearly explain results and recommendations to technical and business stakeholders
• Establish and follow strong engineering practices — code review, reproducibility, experiment tracking, and model documentation
• Deploy, monitor, and maintain models in our containerized Azure environment, applying MLOps principles, including ~~—~~ version control, automated testing, CI/CD, model versioning, and drift detection
• Develop AI-powered tools and applications, including LLM-based solutions (e.g., automating aspects of the modeling process, surfacing insights from model output) for underwriting, claims, and operational use cases
• Contribute to a strong team culture by participating actively in code review and pairing, sharing what you learn, and both providing and seeking feedback to/from team members
• Research, learn, test, and apply new techniques to advance the company’s statistical modeling/MLOps/AI engineering capabilities
• Build strong partnerships within RAD and across the organization, working hand-in-hand with Data and Model Engineering and with our underwriting, claims, and business stakeholders to understand their needs and deliver solutions that create real value

Skills

• 2–5+ years of technical experience in a data science, actuarial, analytics, or predictive modeling role, with hands-on experience deploying models or analytics tools to production
• Strong statistical foundation and analytical skills — able to select, build, validate, and interpret models rigorously, and explain the results clearly
• Proficiency in programming languages such as Python, R, and/or SQL, with the ability to write production-quality code
• Strong knowledge of a variety of modeling techniques and the ability and interest to learn new techniques quickly (e.g., Regression, Classification, Bayesian Modeling, Natural Language Processing, Price Optimization, etc.)
• Experience applying software engineering and MLOps principles — e.g., Git-based workflows, containerization (Docker), CI/CD, model versioning, and monitoring
• Experience with cloud environments (e.g., Azure, AWS) for model development and deployment
• Practical experience building with LLMs and generative AI — e.g., building and using skills, model APIs, prompt-based tools, agent workflows, etc
• Self-starter, quick learner, and creative problem solver that thrives in a flexible, fast-paced, and remote work environment
• P&C insurance domain knowledge, particularly commercial lines and E&S products
• Experience in the end-to-end model creation and deployment process to improve product, pricing, reserving, underwriting, and claims in P&C insurance
• Bachelor's or Master's degree in Mathematics, Statistics, Data Science, Actuarial Science, Computer Science, or related quantitative field
• Experience with a fully containerized model architecture and ML platforms (e.g., Azure ML, MLflow, SageMaker)
• Experience with non-relational (NoSQL) databases and modern data platforms (e.g., Snowflake)
• P&C insurance domain knowledge, particularly commercial lines and E&S products
• Experience in the end-to-end model creation and deployment process to improve product, pricing, reserving, underwriting, and claims in P&C insurance
• Bachelor's or Master's degree in Mathematics, Statistics, Data Science, Actuarial Science, Computer Science, or related quantitative field
• Experience with a fully containerized model architecture and ML platforms (e.g., Azure ML, MLflow, SageMaker)
• Experience with non-relational (NoSQL) databases and modern data platforms (e.g., Snowflake)
• Experience with visualization tools such as Power BI, Shiny, Streamlit, etc

Qualifications

Must Haves

• 2–5+ years of technical experience in a data science, actuarial, analytics, or predictive modeling role, with hands-on experience deploying models or analytics tools to production
• Strong statistical foundation and analytical skills — able to select, build, validate, and interpret models rigorously, and explain the results clearly
• Proficiency in programming languages such as Python, R, and/or SQL, with the ability to write production-quality code
• Strong knowledge of a variety of modeling techniques and the ability and interest to learn new techniques quickly (e.g., Regression, Classification, Bayesian Modeling, Natural Language Processing, Price Optimization, etc.)
• Experience applying software engineering and MLOps principles — e.g., Git-based workflows, containerization (Docker), CI/CD, model versioning, and monitoring
• Experience with cloud environments (e.g., Azure, AWS) for model development and deployment
• Practical experience building with LLMs and generative AI — e.g., building and using skills, model APIs, prompt-based tools, agent workflows, etc
• Self-starter, quick learner, and creative problem solver that thrives in a flexible, fast-paced, and remote work environment
• P&C insurance domain knowledge, particularly commercial lines and E&S products
• Experience in the end-to-end model creation and deployment process to improve product, pricing, reserving, underwriting, and claims in P&C insurance
• Bachelor's or Master's degree in Mathematics, Statistics, Data Science, Actuarial Science, Computer Science, or related quantitative field
• Experience with a fully containerized model architecture and ML platforms (e.g., Azure ML, MLflow, SageMaker)
• Experience with non-relational (NoSQL) databases and modern data platforms (e.g., Snowflake)

Nice to Haves

• P&C insurance domain knowledge, particularly commercial lines and E&S products
• Experience in the end-to-end model creation and deployment process to improve product, pricing, reserving, underwriting, and claims in P&C insurance
• Bachelor's or Master's degree in Mathematics, Statistics, Data Science, Actuarial Science, Computer Science, or related quantitative field
• Experience with a fully containerized model architecture and ML platforms (e.g., Azure ML, MLflow, SageMaker)
• Experience with non-relational (NoSQL) databases and modern data platforms (e.g., Snowflake)
• Experience with visualization tools such as Power BI, Shiny, Streamlit, etc

Benefits

• Annual incentive program
• Health insurance including FSA and HSA options and free access to Teladoc
• Vision insurance
• Dental insurance
• Disability insurance
• Life insurance
• Parental leave
• Responsible time off (unlimited vacation days without an accrual system)
• Paid sick time as required by law
• 401(k)
• Tuition reimbursement
• Employee assistance program
• Remote work environment