2027 Summer Analyst Program - Insurance Risk - Data Science
About The Position
KKR's 2027 Summer Analyst Program is an opportunity to join a leading global investment firm during your graduate career. We are recruiting for Summer Analysts for KKR's Insurance business in our New York office within our Liability Risk business. The Insurance Data Science group reports through the Chief Risk Officer and uses industry-leading machine learning and AI techniques and big data tools to develop predictive models for policy-level transactions and human behaviors. The models are used to develop and price retail products and institutional reinsurance deals, monitor related risk, and to assist in forecasting and financial reporting. The group has a unique vantage point into nearly all aspects of the enterprise and is actively enhancing its capacity, continuing to grow with the whole company. Summer Analysts will gain hands-on exposure across KKR’s insurance platform. Following the conclusion of the internship, 2028 full-time offers may be extended to exceptional performers.
Requirements
- Anticipated graduation date from a master’s program in December 2027 - June 2028.
- Area of study in quantitative discipline such as Computer Science, Engineering, Mathematics, Actuarial Science, or related technical fields.
- Background in a technical or scientific field and at least three years/six semesters of programming experience.
- Proficiency in Python and SQL is required, along with extensive understanding of data structures, statistics, regression, and core machine learning methods.
- Knowledge of Generative AI and modern LLM tooling is required - e.g. building RAG pipelines with vector search, agentic workflows, and tool/function calling (MCP-based integrations).
- Ability to critically evaluate AI-generated outputs for accuracy and relevance is required.
- Comfort using AI tools to improve productivity and quality of work is required.
- Strong analytical, organizational, and communication (written and verbal) skills.
- Proactive, detail oriented, and deadline driven; possess excellent documentation.
Nice To Haves
- Exposure to loop engineering, structured outputs, and evaluating LLM systems is valued.
Responsibilities
- Implement machine learning and optimization tools
- Develop supervised and unsupervised machine learning models
- Build AI solutions for the team and the wider firm
- Assist with ad hoc data analytics projects
- Collaborate to develop the team’s automated data pipeline
Benefits
- Discretionary bonus, based on factors such as individual and team performance.
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What This Job Offers
Career Level
Intern
