Actuarial Senior Data Scientist II

About the Role

Key Responsibilities

• Design and develop advanced insurance pricing models using statistical and machine learning techniques to support strategic pricing decisions and revenue optimization.
• Perform ongoing model validation to ensure robustness, accuracy, and compliance with internal and regulatory standards.
• Monitor model performance over time, identifying drift, degradation, or anomalies, and implement corrective actions as needed.
• Build and deploy analytics solutions that address complex business challenges, leveraging large-scale datasets to generate actionable insights.
• Collaborate closely with cross-functional teams including actuarial, underwriting, and product to align modeling efforts with business goals.
• Communicate findings and recommendations clearly to technical and non-technical stakeholders through presentations, dashboards, and reports.
• Document model development processes, assumptions, and validation results to ensure transparency and reproducibility.
• Support broader team goals and perform additional tasks as needed to drive business success.
• Demonstrate strong teamwork and actively contribute to a positive and inclusive team culture.
• Represent the organization professionally in all interactions with internal and external stakeholders.
• Stay current with industry trends in insurance pricing, data analytics, and machine learning to continuously improve modeling approaches.

Requirements

• 3+ years of experience in insurance data analytics, preferably within the Property & Casualty domain, with a strong understanding of underwriting, claims, and pricing workflows.
• Hands-on experience developing pricing models using statistical, actuarial, or machine learning techniques to support rate-making, segmentation, and profitability analysis.
• Participation in cross-functional initiatives, demonstrating strong collaborative skills and business acumen.
• Strong communication skills, with a track record of presenting technical findings to technical and non-technical stakeholders.
• Proficiency in Python.

Nice to Have

• Solid understanding of actuarial ratemaking principles, including exposure rating, loss cost modeling, and rate adequacy analysis.
• Proficiency in PySpark for distributed data processing and pipeline development.
• Experience with SQL for querying and manipulating large-scale structured datasets.
• Experience with cloud-based analytics environments.
• Experience working with actuarial teams or in a blended actuarial/data science environment.

Qualifications

• Bachelor's degree in a quantitative field such as Statistics, Mathematics, Actuarial Science, Computer Science, Data Science, or a related discipline.
• Progress toward the Associate of the Casualty Actuarial Society (ACAS) designation is highly preferred.

Benefits & Perks

• Hybrid working arrangement with a mix of remote and in-office work.
• 22 weeks of paid leave for family growth, with 12 weeks available to all parents on a gender-equal basis.
• Competitive 401(k) program with company match up to 8%.
• Well-being program including holistic wellbeing coaching, gym membership, confidential counselling, financial and legal advice.
• Tuition Reimbursement for professional certifications and continuing education.
• Employee Network and Community support, including six Employee Networks and community engagement opportunities.