Lead Business Systems Analyst - Actuarial IT

Responsibilities

• Lead with an AI-first perspective to identify opportunities where artificial intelligence, automation, and advanced analytics can improve actuarial systems and processes.
• Partner with actuarial business teams to gather, analyze, and document requirements, with a focus on AI-enabled use cases such as predictive insights, automation, deep research and decision support.
• Translate complex actuarial concepts into clear technical and AI-ready specifications for IT, data, and AI engineering teams.
• Collaborate with AI, data engineering, and platform teams to support AI-driven enhancements, data integrations, and modernization initiatives.
• Define and document requirements for actuarial data usage in AI/ML workflows, including data quality, lineage, and governance considerations.
• Work closely with QA and validation teams to define test scenarios and validate AI outputs and system results against actuarial expectations.
• Serve as a strategic bridge between business outcomes and AI-enabled technical execution, ensuring clarity and alignment throughout delivery.
• Research, evaluate, and propose AI approaches for actuarial modeling, risk assessment, process optimization, and analytics.
• Support change management, documentation, and stakeholder communication related to AI adoption within actuarial functions.
• Promote responsible AI usage, explainability, and transparency in actuarial systems and analytics.

Qualifications

• Bachelor’s degree in business, Information Systems, Mathematics, Actuarial Science, Computer Science, or a related field.
• Proven experience as a Business Analyst in an IT, actuarial, data, or analytics-focused environment.
• Strong understanding of Life, Health, Retirement and Annuity insurance products and actuarial processes.
• Demonstrated ability to translate business and actuarial needs into AI-aware functional and technical requirements.
• Familiarity with data-driven systems, data integrations, and analytics platforms.
• Working knowledge of data analysis tools such as SQL, Excel, and BI platforms.
• Strong analytical thinking, problem-solving, and documentation skills.
• Excellent communication skills, with the ability to engage effectively with actuarial, technical, and business stakeholders.

Preferred Qualifications

• Hands-on experience or strong conceptual understanding of AI and machine learning, including predictive modeling, NLP, or decision intelligence.
• Experience supporting or partnering on AI-enabled initiatives within actuarial, finance, or insurance domains.
• Technical background in software development, data engineering, or analytics.
• Exposure to actuarial or financial data platforms and large-scale data environments.
• Experience with automation, data modernization, or digital transformation initiatives.
• Familiarity with Agile or hybrid delivery methodologies.
• Experience in insurance or financial services organizations.