Principal Data Scientist (Remote)

Responsibilities

• Acquires, organizes, and cleanses structured and unstructured data.
• Conducts in-depth analysis to uncover trends, risks, and business opportunities.
• Applies statistical modeling, machine learning, and advanced analytics to develop predictive and prescriptive solutions.
• Evaluate solution performance using statistically rigorous methods and measure the impact to business outcomes.
• Collaborate with MLOps and IT partners to transition solution prototypes from pilot validation into production environments.
• Ensures ongoing model health through post-deployment monitoring, drift detection, and audit-compliant governance practices.
• Create and communicate results to senior level audiences of varying backgrounds, using business-facing presentations, reports, and dashboards.
• Author and maintain comprehensive technical documentation for data lineage, codebases, results, and production changes.
• Provide technical and project guidance, including peer review of work, for data science team.
• Lead the evaluation of new analytic tools and processes.
• Drive investigation and adoption of advanced machine learning and AI innovations.

Qualifications

• Bachelor’s Degree in Data Science, Statistics, Mathematics, Operations Research, Actuarial Science, Computer Science, Engineering, Physics or related technical field required. Advanced degree preferred.
• 10 years of experience in data science or related advanced analytics domains, including research and teaching, with 3+ years of technical leadership.
• 3+ years of experience supporting underwriting functions, including loss modeling, for Commercial Property (preferred) or Personal Homeowners insurance.
• Demonstrated expertise using Poisson, Gamma, and Tweedie distributions to build loss ratio, pure premium, and frequency–severity loss models for pricing.
• Extensive experience leveraging supervised learning models (e.g., XGBoost, GLM, etc.) and unsupervised techniques (e.g., K-means, PCA, etc.) to solve complex data science problems.
• Advanced Python programming skills supporting data science, including scikit-learn and pandas.
• Proficient data wrangling and ETL abilities using SQL on relational databases.
• Comfortable explaining machine learning models with partial dependence plots and SHAP values.
• Ability to conduct experiments, e.g., A/B Testing, to evaluate the causal impact of model-driven decisions.
• Experience using version control tools such as Git and Azure DevOps.
• Experience working in cloud computing environments such as Azure, AWS, GCP, etc.

Education

Bachelor’s Degree in Data Science, Statistics, Mathematics, Operations Research, Actuarial Science, Computer Science, Engineering, Physics or related technical field required. Advanced degree preferred.

Pay

Actual compensation decision relies on the consideration of internal equity, candidate’s skills and professional experience, geographic location, market and other potential factors. It is not standard practice for an offer to be at or near the top of the range, and therefore a reasonable estimate for this role is between $137,900 and $231,000.