Analyst II

Corporate Actuarial Reserving oversees enterprise-wide reserving related projects, which includes establishing reserve levels, assessing emerging risks, and developing actuarial standards and methodologies.

We are excited to post a position to leverage data science to support enterprise-wide initiatives to strengthen our balance sheet including but not limited to: improving accuracy of reserve estimates for complex segments, demonstrating causal relationships which drive legal systems abuse, and leveraging GenAI to solve a broad range of actuarial and financial challenges.

Corporate Actuarial ensures Liberty’s financial strength by producing insights, in collaboration with SBU actuarial partners, which inform the CFO and executive Reserve Committee.  As a member of the team, you will have an exciting opportunity to, in partnership with actuarial talent, develop innovative solutions to our rapidly evolving challenges.

Successful candidates will possess a solid understanding of insurance concepts, demonstrate hands-on experience with data manipulation, exploratory data analysis, and advanced machine learning techniques. Intellectual curiosity and innovative critical thinking are essential for understanding business challenges and translating them into impactful data science opportunities that produce actionable insights. Strong communication and interpersonal skills are crucial for effectively conveying comprehensive data science solutions to non-technical audiences.

Responsibilities

• Leverages robust understanding of internal partners’ needs, in collaboration with cross-functional teams to develop innovative solutions and produce actionable insights
• Clearly and concisely communicates findings and insights to non-data science business partners.
• Works with partners to identify trade-offs among potential solutions with respect to efficiency, accuracy, and other relevant performance metrics.
• Applies best data science practices to fully explore large structured and unstructured datasets, engineer optimal features, and execute cutting-edge algorithms.
• Delivers robust analysis, leveraging innovative and accessible visuals.
• Regularly engages with the data science community and participates in cross-functional working groups.

• Demonstrated ability to leverage business knowledge to produce effective solutions. Understanding of insurance and reserving operations preferred.
• Demonstrated ability to develop and manage predictive models (e.g. GLMs, GBMs, NLP) and exposure to GenAI preferred.
• Demonstrated coding proficiency in programming languages such as Python, R, or SAS, with a strong grasp of data science libraries and frameworks.
• Hands-on experience leveraging large datasets to support data science solutions.
• Strong verbal and written communication skills, and ability to exchange ideas and convey complex information clearly and concisely.
• Curiosity and creativity in problem solving, with the ability to translate business challenges into data science solutions and deliver valuable insights.
• Demonstrated ability to collaborate with cross-functional team, interact with business stakeholders, and articulate data science solutions to non-technical audiences.
• Competencies typically acquired through 0-1 yrs. of related experience with a Ph.D., a minimum of 2-3 yrs. of experience with a master’s degree, a minimum of 4+ yrs. of experience with a bachelor’s degree.