Operations & Analytics Associate

POSITION SUMMARY

KKR is hiring for an enterprise Data Operations group to collect, manage, and harness the power of data across our diverse business activities. The Data Operations Center of Excellence (CoE) is a cross-functional team dedicated to formulating and driving KKR's enterprise data strategy while also providing the operating leverage required to bring these strategies and frameworks to life.

The Data Operations CoE is seeking to hire an Associate / Senior Analyst to support Analytics efforts across Private Markets and Credit. The candidate will work closely with business stakeholders and technology partners to build analytical models, data products, and lightweight tools that go beyond static reporting, translating complex data into clear, actionable insight for investment and operational decision-makers. This is a hands-on role where the candidate should expect to be writing SQL and Python, building and testing models, and developing tools directly. 

The ideal candidate would have the unique combination of strong data analysis and data science skills, genuine comfort building tools and applications, and the interpersonal polish to engage confidently with senior leadership. The candidate should have a passion/interest in private markets and credit investing, an interest in embracing new technologies (AI), strong verbal/written communication skills, and be a good cultural fit with an emphasis on collaboration, excellence, and action-oriented results. 

RESPONSIBILITIES

• Design, build, and maintain analytical models, data products, and lightweight tools that support Private Markets and Credit investment teams, going beyond static reporting to surface original, actionable insight 
• Serve as a key liaison between business stakeholders and technology teams, gathering requirements, defining analytical use cases, and ensuring delivered solutions meet business needs 
• Write and optimize complex SQL queries and Python-based scripts to extract, transform, model, and analyze data across multiple sources and platforms, ensuring data quality and consistency 
• Partner closely with data engineering, technology, and operations teams to design and implement scalable data pipelines, integrations, and infrastructure that underpin analytics, modeling, and tool development 
• Develop domain expertise in private markets and credit data, including deal, portfolio, fund, and investor data, and apply that knowledge to improve data coverage, quality, and analytical depth 
• Identify opportunities to streamline manual workflows, automate repetitive tasks, and improve the efficiency and reliability of data processes across the team 
• Explore and apply AI tools, large language models, and emerging technologies to build new analytical capabilities and unlock new insight for the business 
• Collaborate with team members across offices and time zones in support of these initiatives 

QUALIFICATIONS

• 4+ years of hands-on experience in data analytics, data science, or a related field, ideally within financial services, private equity, credit, or a comparable institutional environment 
• Strong proficiency in SQL and Python, with demonstrated ability to independently build data models, analytical pipelines, and tools  
• Hands-on experience with Snowflake (or equivalent cloud data warehouse) and BI/reporting tools (e.g., Power BI, Sigma, Tableau) as part of a broader analytical toolkit 
• Demonstrated ability to work in business-facing roles, translating stakeholder needs into analytical frameworks & tools 
• Excellent verbal and written communication skills, with the ability to distill complex data into insight for both technical and non-technical audiences 
• Intellectual curiosity and interest in private markets, credit, and alternative investments 
• Strong cultural fit – collaborative, intellectually curious, action-oriented, and committed to high standards of excellence and accountability 
• Ability to thrive in a fast-paced environment, with a proactive, self-starter mindset and high attention to detail 

PREFERRED QUALIFICATIONS

• Direct experience in private markets, credit, or alternative investment data and analytics or background in financial services, asset management, or fintech 
• Experience building internal applications or tools (e.g., Python-based apps, low-code platforms, or AI-assisted development) to deliver data products beyond dashboards 
• Hands-on experience applying AI, machine learning, or large language models to improve business workflows and data processes 
• Working understanding of dbt for managing data transformations, building modular analytics pipelines, and maintaining well-tested, version-controlled data models 
• Experience with version control systems (e.g., Git) and collaborative development workflows 

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