Senior AI/ML Engineer

*Starr Insurance Companies is a leading insurance and investment organization, providing commercial property and casualty insurance, including travel and accident coverage, to almost every imaginable business and industry in virtually every part of the world.

Cornelius Vander Starr established his first insurance company in Shanghai, China in 1919. Today, we are one of the world’s fastest growing insurance organizations, capable of writing in 128 countries on 6 continents.* Join the Starr Enterprise Data and Artificial Intelligence Organization and start reimagining the future of insurance. The Data and AI team at Starr builds first-of-a-kind capabilities that advance the insurance practice and scale across the entire enterprise. The team’s ultimate mission is to develop cutting-edge data and AI capabilities that drive profit growth for Starr.

The Senior AI/ML engineer is an important, integral part of the Data & AI team. This position is responsible for uncovering meaningful data patterns and transforming them into actionable insights by leveraging predictive modeling, data mining, machine learning algorithms, and foundational models. This individual will be responsible for developing scalable solutions to provide data-driven and optimization insights. He/she should have vast experience in machine learning/AI algorithms and demonstrated ability to innovate and customize when necessary. We are looking for somebody who will be passionate about learning and deploying leading technologies in the AI space specific to the business needs to drive results and identify opportunities. As a Senior AI/ML Engineer this person will drive business impact by solving unique problems through analytics and machine learning, continuous improvement in methodologies, and change management in a fast-paced environment.

Key Responsibilities

• Design, develop, and deploy AI/ML solutions with best practices in statistics, machine learning, deep learning, and foundational models to improve the profitability for Starr. Example includes classification models, forecasting, propensity and uplift modeling, foundational model fine-tuning, evaluation, and implementation, etc.
• Identify growth opportunities in underwriting, claims processing, risk assessment, and/or customer service through AI/ML augmentation.
• Collaborate cross-functionally with business, IT, and Transformation to drive scalability and impact of the AI/ML solutions.
• Communicate complex AI/ML concepts and findings to business leaders in a clear and concise manner.
• Conduct research and stay up-to-date with the latest advancements in AI/ML to continuously improve our AI capabilities.

Required Professional and Technical Expertise:

• Master’s degree in Statistics, Data Science, Mathematics, Computer Science, Operational Research, or related disciplines.
• 5+ years’ experience with data science/machine learning techniques (e.g., logistic regression, hierarchical regression, decision tree, random forest, neural networks, etc.) and 2+ years of experience working with LLM.
• Expertise in Python, SQL and with data science and data analytics packages working on structured and unstructured data.
• Experience with developing and industrializing scalable AI solutions from ideation to delivery.
• Expertise working in Azure, AWS or other cloud service using big data solutions.
• Proven ability to understand, cleanse, and integrate massive disparate data sets and demonstrated familiarity with data modeling workflow.
• Recognized for analytical rigor and ability to identify actionable insights from ambiguous and sometimes limited information.
• Strong communication, ability to effectively connect/translate complex analytics findings to business insights and recommendations.

Preferred Professional and Technical Expertise:

• Ph.D. in Statistics, Data Science, Mathematics, Computer Science, Operational Research, or related disciplines.
• Natural language processing and natural language understanding expertise.
• Ability to gain consensus, to lead change and transformation.
• Passionate about data science and self-motivated to stay abreast of advances in data science techniques.
• Desire to work in a team based dynamic and fast-paced business culture.
• Experience leading projects for one or more business units.
• Experience in the insurance industry, particularly in underwriting, claims processing, or risk management.
• Knowledge of actuarial science and insura…