RGA is looking to drive the strategic direction and execution of AI, machine learning, and advanced analytics initiatives across the region to enhance business operations, improve decision-making processes, and create competitive advantages.
Requirements
- Strong background in statistical modeling, machine learning algorithms, and data engineering principles.
- Expert knowledge of modern data science tools, cloud platforms, and big data technologies.
- 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.
- 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.
Responsibilities
- Continue to develop, support, and execute the region’s long-term strategy for AI, machine learning, and data science initiatives.
- Oversee the end-to-end lifecycle of multiple concurrent data science projects.
- Ensure timely delivery of high-quality, scalable solutions that meet business requirements.
- Stay at the forefront of AI, machine learning, and statistical modeling advancements.
- Evaluate and recommend new technologies, methodologies, and tools to enhance the team's capabilities.
- Provide technical guidance and expertise on complex data science problems.
- Continue to advance RGA’s data science and AI technology and supporting infrastructure by partnering with Global Technology.
Other
- 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.
- 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.
