VP, AI & Emerging Analytics
Reinsurance Group of AmericaAurora, CO, US18 hours ago
Job type
- Full-time
Job descriptionBachelor's degree in Computer Science, Math, Statistics, Actuarial Science, Finance, Economics or related field. 15+ years of analytics experience or in developing statistical models for insurance or related applications. Proven track record of successfully leading large-scale AI and machine learning initiatives in a Fortune 500 environment. Deep understanding of insurance industry dynamics and challenges, with 5+ years of experience in the sector. Strong background in statistical modeling, machine learning algorithms, and data engineering principles. Experience in managing and scaling data science teams. Exceptional leadership skills with the ability to inspire and motivate high-performing technical teams. Strong strategic thinking and ability to translate business problems into data science solutions. Expert knowledge of modern data science tools, cloud platforms, and big data technologies. Excellent communication skills, able to explain complex technical concepts to both technical and non-technical audiences. Strong product management skills with the ability to manage multiple complex initiatives simultaneously. Deep understanding of data governance, ethics, and regulatory compliance in the context of AI and machine learning. Strong understanding of large language models, transformer architectures, and modern generative AI systems, combined with the ability to evaluate model capabilities, limitations, and appropriate use cases for business applications. Ability to balance technical expertise with business acumen to drive value creation. Strong negotiation and conflict resolution skills. Adaptability and resilience in a fast-paced, evolving technological landscape. Capacity to translate AI capabilities into real-world products while navigating complex ethical considerations around safety, bias, privacy, and responsible deployment at scale. Highly Advanced ability to translate business needs and problems into viable / accepted solutions. Highly Advanced ability to liaise with individuals across a wide variety of operational, functional and technical disciplines. Master's degree or PhD in Statistics, Actuarial Science, Business, Finance, Economics, or related field. 10+ years of experience with statistical modeling for insurance (Decision Trees, Time Series, Regression, reinforcement learning, unsupervised learning algorithms, etc.). 5+ years of experience in working with and deploying generative AI technologies into an enterprise setting. Knowledge of reinsurance, life insurance, and financial markets. Proficiency in multiple programming languages such as Python, R, and SQL. Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). Strong knowledge of cloud computing platforms (e.g., AWS, Azure, GCP) and their ML / AI services. Experience with big data technologies such as Snowflake, Databricks, Spark, and distributed computing. Proficiency with modern frameworks like LangChain, LangGraph, DSPy, or LlamaIndex for building complex AI workflows, multi-step reasoning chains, and agentic systems that combine LLMs with tools, memory, and structured decision-making processes. Understanding of DevOps and MLOps practices for model deployment and monitoring. Knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes). Experience with graph databases and network analysis techniques. Familiarity with natural language processing (NLP) and computer vision algorithms and applications. Understanding of time series analysis and forecasting methods relevant to the insurance industry. Knowledge of actuarial concepts including mortality, morbidity, and persistency studies. Knowledge of life, health, and / or annuity products. Knowledge of life insurance underwriting and biometric risk analysis. Knowledge of insurance risk analysis. Experience in computational finance, econometrics, statistics and math. Gain valuable knowledge from and experience with diverse, caring colleagues around the world. Enjoy a respectful, welcoming environment that fosters individuality and encourages pioneering thought. Join the bright and creative minds of RGA, and experience vast, endless career potential.
Vice President Of Ai And Emerging Analytics
RGA is a purpose-driven organization working to solve today's challenges through innovation and collaboration. A Fortune 200 Company and listed among its World's Most Admired Companies, we're the only global reinsurance company to focus primarily on life- and health-related solutions. Join our multinational team of intelligent, motivated, and collaborative people, and help us make financial protection accessible to all.
Position Overview
The Vice President of AI and Emerging Analytics is a leadership role responsible for driving the strategic direction and execution of AI, machine learning, and advanced analytics initiatives across the region. This position leads a team of data scientists, machine learning engineers, and data engineers to develop and implement cutting-edge, data-driven solutions that enhance business operations, improve decision-making processes, and create competitive advantages for RGA.
Responsibilities
- Strategic Leadership
- Team Management and Development
- Project Oversight and Delivery
- Technical Leadership and Innovation
- Stakeholder Management and Communication
- Governance and Compliance
- Financial Management
- Technology and Infrastructure
Requirements
Preferred
What You Can Expect From RGA :
Compensation Range :
$175,650.00 - $261,600.00 Annual
Base pay varies depending on job-related knowledge, skills, experience and market location. In addition, RGA provides an annual bonus plan that includes all roles and some positions are eligible for participation in our long-term equity incentive plan. RGA also maintains a full range of health, retirement, and other employee benefits.
RGA is an equal opportunity employer. Qualified applicants will be considered without regard to race, color, age, gender identity or expression, sex, disability, veteran status, religion, national origin, or any other characteristic protected by applicable equal employment opportunity laws.
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