The Associate Data Scientist supports data-driven decision-making across the organization by developing and applying statistical and machine learning models to insurance data. This role is responsible for data extraction, cleaning, and exploratory analysis, as well as building predictive models to support initiatives across the organization such as risk assessment, claims forecasting, pricing, and fraud detection. Working closely with senior data scientists and supervisors, the Associate Data Scientist translates complex data into actionable insights while ensuring model transparency, regulatory compliance, and alignment with business objectives. This position provides an opportunity to contribute to pricing, claims, and underwriting strategies, operational efficiency, and improved customer outcomes within a highly regulated, risk-focused environment.

Duties & Responsibilities:

Extract, clean, and prepare structured insurance data from multiple sources for analysis and modeling Perform exploratory data analysis to identify trends, patterns, and anomalies in risk, claims, and customer data Develop, validate, and maintain predictive models to support initiatives across the organization such as risk assessment, claims forecasting, pricing and fraud detection. Evaluate model performance and ensure outputs are accurate, reliable, and aligned with business objectives Collaborate with senior team members and cross-functional stakeholders to translate business problems into analytical solutions Communicate findings through reports, visualizations, and presentations to technical and non-technical audiences Ensure compliance with regulatory requirements, data governance standards, and model transparency expectations Support continuous improvement of data pipelines, analytical processes, and model performance

Requirements:

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Actuarial Science, or a related field required 0-3 years of experience in data analysis, data science, or a related role

Qualifications/Skills:

Proficiency in SQL for data extraction and manipulation Experience with Python (preferred) or R for data analysis and modeling Familiarity with statistical methods and machine learning techniques Experience with data visualization tools (e.g., Tableau) preferred Knowledge of data structures, ETL processes, and data quality practices

Analytical Thinking:

Ability to interpret complex data and develop meaningful insights

Problem Solving:

Applies structured approaches to solve business and analytical challenges

Communication:

Clearly conveys technical concepts to diverse audiences

Collaboration:

Works effectively with team members, analysts, and business stakeholders Attention to

Detail:

Ensures accuracy and integrity of data, models, and reporting

Adaptability:

Learns new tools, techniques, and business concepts quickly

Business Acumen:

Understands insurance concepts such as risk, pricing, and claim

Market Range:

12 / Exempt / 40 hours per week / Hybrid - 2 days in office

Salary:

$73,848 - $123,080 Accepting applications through: 9/3/26