Remote Senior Predictive Analyst | WFH

Job Overview We are seeking a highly skilled Senior Predictive Analyst to join our esteemed organization in the property and casualty insurance sector. Our commitment to excellence drives our mission to provide superior service to our agents and clients, and your analytical expertise will be instrumental in advancing our data-driven decision-making processes. Key Responsibilities • Design and sustain comprehensive predictive models employing sophisticated statistical and machine learning methodologies that inform our underwriting, pricing, and claims management strategies. • Conduct in-depth data analysis to identify trends, patterns, and outliers within our datasets. • Ensure the reliability and accuracy of predictive models through rigorous validation and documentation practices, in compliance with industry standards. • Maintain detailed records of modeling approaches, assumptions, and outcomes. • Collaborate with data engineering teams to guarantee data quality and integrity. • Utilize data cleansing techniques to rectify any discrepancies within the data. • Work alongside cross-functional teams, including actuaries, underwriters, claims specialists, and IT personnel, to gather analytical requirements and develop actionable solutions. • Articulate findings and insights to both technical and non-technical audiences, providing clear and actionable recommendations. • Establish processes to monitor model performance, recommending adjustments and enhancements as necessary. • Stay abreast of best practices and emerging trends in predictive modeling within the insurance industry. • Ensure compliance with industry regulations while assisting in the preparation of documentation for regulatory submissions. • Identify and implement opportunities for enhancing efficiency and accuracy in predictive modeling workflows. • Mentor and guide junior analysts, fostering their professional growth and development. Required Skills • Proficient in advanced statistical software (e.g., R, Python, SAS) as well as data manipulation tools (e.g., SQL). • Extensive experience in complex predictive modeling techniques, including regression analysis and machine learning algorithms, with a proven ability to innovate. • Strong analytical, problem-solving, and critical thinking capabilities. • Excellent communication skills to effectively translate complex concepts for non-technical stakeholders. Qualifications • Bachelor's degree in Statistics, Mathematics, Actuarial Science, Data Science, or a related domain; a Master's degree is preferred. • 4-6 years of progressive experience within predictive modeling, data analysis, or a related field in the insurance industry, demonstrating leadership and advanced problem-solving skills. Career Growth Opportunities This role presents significant potential for professional development, including opportunities to nurture junior talent and stay informed about industry best practices and emerging trends. Company Culture And Values Our organization is dedicated to fostering a collaborative and inclusive workplace, where innovation and professional growth are paramount. We believe that a diverse team contributes to our overall success and service excellence. Compensation And Benefits • 401(k) Retirement Savings Plan with employer matching • Comprehensive Medical, Prescription Drug, Vision, and Dental Insurance • Paid Time Off, Holidays, and Leave Programs • Flexible Spending Accounts • Basic Life Insurance and Voluntary Life/ADD • Voluntary Short-Term and Long-Term Disability Please note that the salary range provided is an estimate and may not reflect the actual compensation for this role. Final salary discussions will take place during the interview process. We are an Equal Opportunity Employer, committed to fostering a diverse and inclusive workplace. All employment decisions are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, family status, or any other status protected by applicable laws. Employment Type: Full-Time