We are seeking a skilled Data Scientist to focus on developing and monitoring models used in multivariate analysis, linear modeling, and data mining. This role involves creating and testing predictive risk models, and effectively communicating complex mathematical and computational learning concepts to relevant staff. Additionally, the Data Scientist will align modeling efforts with business goals and capital strength, offering strategic recommendations to enhance business processes.
Responsibilities
Predictive Modeling & Analysis:
Provide technical and quantitative analysis for the predictive modeling group.
Conduct statistical data mining and actuarial research using advanced statistical methods.
Utilize computer technology, modeling tools, and programming languages for analysis.
Lead projects requiring advanced statistical analysis, research, and mathematical calculations.
Apply predictive modeling techniques to research and interpret data, identifying correlations through univariate and multivariate analysis.
Model Development & Deployment:
Develop custom, explainable models that enhance business processes in alignment with corporate goals and market conditions.
Document model requirements and analyze data to determine the optimal modeling approach.
Identify candidate risk factors and build models using training, test, and cross-validation datasets.
Share and finalize model results, deploying and maintaining models with or without IT support.
Communication & Training:
Present findings and recommendations to relevant stakeholders and prepare summary reports.
Communicate model results and train users on their interpretation and application.
Additional Responsibilities (for Data Scientist II):
Oversee the creation, development, and maintenance of predictive models.
Facilitate communication of predictive model results across departments and assist in implementing results into systems.
Mentor Predictive Modeler I and participate in setting annual budgets, goals, and objectives.
Qualifications
Education:
Bachelor’s degree in insurance, mathematics, economics, statistics, or computer science required.
Advanced degree in statistics, actuarial science, or applied mathematics preferred.
Continuous learning is encouraged, with certifications or progress toward certification highly preferred.
Experience:
Data Scientist I:
No prior experience required with relevant educational credentials; however, experience in workers compensation, predictive modeling, and actuarial science is preferred.
Data Scientist II:
Minimum of 2 years of experience in research, modeling, or actuarial roles required, with a preference for experience in workers compensation.
Demonstrated expertise in statistical modeling, data mining techniques (e.g., GLM, clustering, decision trees), and insurance-related data.
Skills & Abilities:
Strong interpersonal, organizational, and communication skills.
Proficiency in computer software relevant to the role, including SAS, R, and SQL.
Excellent database management skills and project management capabilities.
Ability to provide direction to department analysts and work independently with minimal supervision.
Resourceful problem-solving skills, creativity, and the ability to handle multiple projects and deadlines.
Knowledge of insurance and underwriting techniques, and ability to maintain confidentiality.
Strong logical thinking skills to define problems, collect data, and make actionable recommendations.
Working Conditions
This role is based in an office setting with no unusual hazards.
Compensation
The salary range for this position is between $67,500 and $113,100, depending on factors such as internal equity, candidate experience, geographic location, and market conditions. Compensation offers are typically based on a range and not at the top end of the scale.
Equal Opportunity Employer
We value diversity and are committed to providing equal employment opportunities. We do not tolerate discrimination or harassment in any form. This position is offered on an “at will” basis, and nothing in this description is intended to create a contractual obligation.
