Data Scientist - Remote

We are seeking an experienced Data Scientist to support advanced predictive modeling, statistical analysis, data mining, and analytical research initiatives. The primary focus of this role is the development, implementation, monitoring, and maintenance of models used in multivariate analysis, statistical modeling, predictive analytics, and data mining.

This position will be responsible for developing and testing predictive risk models, identifying meaningful relationships and patterns within complex datasets, and translating sophisticated mathematical and computational concepts into clear, actionable recommendations.

The Data Scientist will also work closely with business and technical stakeholders to understand organizational goals, evaluate business processes, and provide strategic recommendations that support growth, operational effectiveness, and overall corporate objectives., * Provide technical and quantitative analysis supporting predictive modeling initiatives.

• Perform statistical data mining and analytical research using advanced statistical methodologies.
• Develop, test, validate, implement, and monitor predictive and statistical models.
• Conduct advanced statistical analyses, mathematical calculations, and research requiring a high degree of technical expertise.
• Analyze data and identify patterns, trends, relationships, and correlations using both univariate and multivariate analysis.
• Develop custom, explainable models that enhance business processes and reflect organizational goals, experience, and current market conditions.
• Apply techniques including pattern recognition, evolutionary computation, statistical modeling, data mining, and machine learning algorithms.
• Document model requirements, methodologies, assumptions, results, and maintenance procedures.
• Oversee the development, implementation, maintenance, and ongoing monitoring of analytical and predictive models.
• Perform ad hoc analyses to identify issues or opportunities related to existing models.
• Design and lead implementation efforts for model maintenance procedures.
• Support the deployment and ongoing maintenance of models, with or without assistance from the IT department.
• Participate in the implementation of predictive model results into appropriate business systems and processes.
• Interpret analytical findings and determine appropriate actionable steps based on model results.
• Present findings, recommendations, and model results to business, technical, and executive stakeholders.
• Prepare and deliver reports, presentations, and other documentation communicating analytical findings and model results.
• Communicate complex mathematical, statistical, and computational concepts in a clear and understandable manner.
• Train users on model results, analytical methodologies, and appropriate interpretation of findings.
• Provide direction and mentorship to other analysts regarding modeling and analytical activities.
• Collaborate with analysts, IT teams, business stakeholders, and other affected departments to successfully implement analytical solutions.
• Manage multiple analytical and modeling projects while meeting established deadlines and business requirements.

• Bachelor’s degree in Insurance, Mathematics, Economics, Statistics, Computer Science, or a related quantitative discipline.
• 4-6 years of experience in research, modeling, statistical analysis, or a closely related analytical field.
• Healthcare payer experience is required.
• Strong knowledge of advanced statistical modeling and data mining techniques.
• Experience developing, testing, validating, deploying, and monitoring predictive models.
• Experience conducting univariate and multivariate statistical analyses.
• Strong hands-on experience with Python.
• Strong hands-on experience with SQL.
• Strong database management and data manipulation skills.
• Experience working with large and complex datasets.
• Strong understanding of predictive modeling methodologies, statistical analysis, and advanced analytical techniques.
• Ability to apply independent logical thinking to define problems, collect and evaluate data, establish facts, draw valid conclusions, and make actionable strategic recommendations.
• Strong analytical, quantitative, critical-thinking, and problem-solving skills.
• Excellent interpersonal, organizational, written, and verbal communication skills.
• Ability to clearly communicate complex analytical and statistical concepts to both technical and non-technical stakeholders.
• Ability to independently manage multiple projects, establish workflows, prioritize responsibilities, and meet required deadlines.
• Ability to work effectively both independently and as part of a collaborative team.
• Ability to exercise independent judgment, initiative, creativity, and discretion with minimal supervision.
• Ability to provide direction and guidance to other analysts.
• Resourceful problem-solving skills and a strong desire to achieve successful business outcomes.
• Knowledge of insurance and underwriting concepts, including agency and policyholder needs., * Advanced degree in Statistics, Actuarial Science, Applied Mathematics, or another closely related quantitative discipline.
• Professional certification or demonstrated progress toward relevant certification.
• Advanced experience with statistical modeling, data mining, machine learning, and predictive analytics.
• Experience leading analytical or modeling initiatives and providing guidance to other analysts.
• Experience communicating model results and recommendations to senior-level stakeholders.

Technical Skills

Candidates should have general familiarity and practical experience with the following:

• Python
• SQL
• Statistical modeling
• Predictive modeling
• Data mining
• Machine learning
• Multivariate and univariate analysis
• Database management
• Data manipulation
• Mathematical and statistical analysis
• Model development, deployment, monitoring, and maintenance
• Spreadsheet applications and other analytical software tools

Working Conditions

• Work is performed in an office setting with no unusual hazards.
• Minimal travel may be required.