Senior Associate at PwC focusing on data analytics to drive insights and guide client strategies. Involves advanced techniques and collaboration on AI and GenAI solutions.
About the role
- Director leading Workers’ Compensation Pricing Models within Actuarial group, driving innovation in predictive modeling, machine learning, and actuarial analytics for significant business line.
Responsibilities
- Lead WC Modeling: Serve as the model owner for Workers’ Compensation predictive models, ensuring alignment with pricing and business priorities.
- Partner on strategic vision while managing team capacity and driving timely model deliverables.
- Model Development & Deployment: Lead design, maintenance, and deployment of predictive models for frequency, severity, and loss cost estimates, ensuring production readiness and effective integration into pricing workflows.
- Cross-Functional Collaboration: Partner with Actuarial, Data Engineering, Underwriting, and Product teams to connect modeling initiatives with pricing strategies and organizational goals, promoting shared problem-solving.
- Innovation: Drive modernization through advanced modeling techniques, machine learning, and AI to enhance efficiency and decision-making.
- Lead experimentation with new data sources, features, and methodologies to uncover insights and advance strategic objectives.
- Operational Excellence: Ensure robust documentation, validation, and governance, along with scalable processes to monitor model performance and maintain reliability.
- Talent Development: Mentor and develop team members, fostering a culture of curiosity, ownership, and continuous learning.
- Support hiring and onboarding, including intern and actuarial student rotations.
- Strategic Influence: Participate in enterprise initiatives to ensure Workers' Compensation predictive models are efficiently integrated into core data and system platforms.
Requirements
- 8+ years of relevant analytical experience
- Master’s or Ph.D. in Statistics, Applied Mathematics, Quantitative Economics, Actuarial Science, Data Science, Computer Science, or a similar analytical field, or a relevant professional designation (e.g. FCAS, FSA, CSPA, ACAS, ASA)
- Expertise in statistical modeling, inference, and building machine learning algorithms in Python and/or R
- Expertise in the end-to-end modeling lifecycle, from requirements gathering to monitoring and validation.
- Experience in SQL and familiarity with cloud-native environments (e.g., Snowflake, Sagemaker).
- Able to communicate effectively with both technical and non-technical audiences.
- Able to translate complex technical topics into business solutions and strategies as well as turn business requirements into a technical solution.
- Prior Management Experience Highly Preferred
Benefits
- Short-term or annual bonuses
- Long-term incentives
- On-the-spot recognition
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
Data Scientist responsible for analyzing complex data sets and developing methods to create actionable insights. Collaborate with engineering teams to improve data quality and deliver business value.
Senior Director driving product development in data science for TransUnion. Leading initiatives in AI and analytics for the Specialized Risk portfolio.
Data & Analytics Lead at AstraZeneca driving data - driven solutions in clinical product development. Leading teams and collaborating with stakeholders across global platforms.
Mid - Level Engineering Data Scientist for Boeing's Global Services Analytics team. Creating analytics models and collaborating on health management solutions for KC - 46 platform.
AI expert managing predictive modeling and statistical validation for TEHORA. Integrating predictive models into API architecture and producing performance metrics.
Head of Data Strategy leading and developing data initiatives for Zurich's GI Business. Focusing on data strategy, governance, and analytics while fostering collaboration across teams.
Medical Analyst analyzing engagement effectiveness with advanced analytics solutions aligned with Medical business strategies. Collaborating with cross - functional teams to provide insights for US Medical Affairs.
EU
Research Fellow/Trainee in Women's Health using Data Science and Health Information Technology. Developing interdisciplinary research skills and methodologies focusing on health research.
Senior Data Scientist developing Asset Management Analytics for Queensland Rail. Contributing to organisational KPIs and enhancing asset performance through data analysis and modelling.