Data Operations - Distribution Data Enablement Lead

COMPANY OVERVIEW

KKR is a leading global investment firm that offers alternative asset management as well as capital markets and insurance solutions. KKR aims to generate attractive investment returns by following a patient and disciplined investment approach, employing world-class people, and supporting growth in its portfolio companies and communities. KKR sponsors investment funds that invest in private equity, credit and real assets and has strategic partners that manage hedge funds. KKR’s insurance subsidiaries offer retirement, life and reinsurance products under the management of Global Atlantic Financial Group. References to KKR’s investments may include the activities of its sponsored funds and insurance subsidiaries.

TEAM OVERVIEW

KKR’s Global Data Operations team is responsible for collecting, managing, governing, and harnessing data across the firm. Within Data Operations, the Data Operations Center of Excellence (CoE) operates as a hub-and-spoke data delivery engine, pairing functional spokes with deep business expertise and a central delivery hub with scalable data, analytics, governance, reporting, and core data management capabilities.

The Distribution Data Enablement team is the functional spoke supporting KKR’s Distribution organization, delivering trusted data and analytics solutions across client and LP data management, operational controls and reconciliations, fund performance, LP outcomes, relationship economics, fundraising trends, and broader business performance across asset classes.

POSITION OVERVIEW

We are seeking a Principal-level Distribution Data Enablement Lead to serve as the primary data and analytics partner for Distribution business performance, fund performance analytics, LP-level insights, and cross-asset-class commercial intelligence.

This role will help define and build a quantitative, forward-looking, and solution-oriented data enablement capability for Distribution. The individual will be responsible for developing scalable analytics, models, tools/automation, and data solutions that support decision-making across fundraising, product strategy, investor engagement, fund performance, LP outcomes, relationship economics, and broader commercial performance.

The successful candidate will design, build and lead advanced analytical capabilities, including the Python-based models, applications, automation, and self-service tools required to operationalize the function. These capabilities will help Distribution answer complex questions such as how fund performance changes if specific deals are included or excluded, how outcomes compare across strategies, how co-investment participation affects investor outcomes, how LP relationships perform economically over time, where profitability is concentrated across the client base, and how fundraising, product, and investor trends are evolving across the platform.

This is a highly hands-on technical leadership role. The individual must be able to partner with senior Distribution, Product Strategy, Finance, Investment, and Data/Technology stakeholders while personally building models, prototyping analytical tools, automating workflows, and modernizing the firm’s Distribution data and analytics environment. The role will require strong technical execution, commercial judgment, and the ability to influence strategic architecture decisions as the capability is built out.

RESPONSIBILITIES

Serve as the primary analytics partner for Distribution business performance, fund performance analytics, LP-level insights, and investor economics

Lead the evolution of the historical Performance Analytics function from a private markets-focused reporting capability into a broader cross-asset-class Distribution advanced analytics and data enablement function

Build analytical models, Python-based data applications, automation, and self-service tools that enable scalable insight generation rather than one-off analysis

Deliver high-quality ad-hoc analysis, performance insights, hypothetical scenarios, investor analytics, and business performance reporting for senior Distribution stakeholders

Build reusable models that evaluate fund performance under different hypothetical scenarios, including inclusion or exclusion of specific deals, co-investment participation, investment timing, cash flow assumptions, and portfolio composition changes

Develop LP-level analytics across asset classes, including investor performance, exposure, allocation, capital activity, product participation, and relationship-level economics

Build profitability and commercial performance analytics for LP relationships, including revenue, economics, resource intensity, product participation, and long-term relationship value

Support macro-Distribution business performance analysis, including fundraising trends, platform economics, investor segmentation, product performance, and concentration across LPs, channels, regions, and strategies

Integrate Distribution, fund, investor, deal, finance, and accounting data to create richer analytical views of investor outcomes and business performance

Modernize manual and Excel-heavy performance analytics processes through reusable models, governed datasets, standardized calculations, and automated workflows

Partner with Technology and Data Operations to productionize prototypes, improve data pipelines, and strengthen the broader Distribution analytics infrastructure

Translate complex fund, deal, LP, and commercial data into clear insights, executive-ready narratives, and decision-support materials

Establish quality controls, documentation, and governance standards for recurring analytics, scenario models, dashboards, and decision-support tools

Help define the long-term operating model for Distribution data enablement, including service model, toolset, prioritization framework, data standards, and partnership model with Product Strategy, Finance, Technology, and Distribution stakeholders

QUALIFICATIONS

10+ years of experience in investment analytics, performance analytics, investor analytics, quantitative analytics, financial analysis/ engineering, business performance analytics, or related roles within asset management, alternatives, investment banking, or financial services

Deep understanding of private markets performance concepts/metrics, including fund structures, LP reporting, capital activity, valuations, fund cash flows, IRR, MOIC, TVPI, DPI, PME, benchmarking, performance attribution models, and deal-level contribution analysis

Strong cross-asset-class orientation, with the ability to extend fund, investor, and business performance analytics across private equity, credit, real estate, infrastructure, insurance-related strategies, and other investment products

Experience developing hypothetical and scenario-based analysis, including deal inclusion/exclusion, co-investment impact, cash flow projections, portfolio construction changes, and LP-specific performance scenarios

Strong understanding of LP-level analytics, including investor exposure, product participation, capital commitments, unfunded balances, subscriptions, redemptions, distributions, realized/unrealized performance, and relationship economics

Experience with business performance or profitability analytics, including client profitability, revenue attribution, relationship value, platform economics, segmentation, concentration, and commercial trend analysis

Familiarity with financial books and records, fund accounting, investment accounting, and performance data environments; experience with platforms such as Investran, Geneva, Salesforce, or similar systems preferred

Highly hands-on technical coding skills, including advanced Python capability and experience building analytical tools, applications, automation, reusable models, and scalable reporting solutions

Advanced SQL and database manipulation skills, with the ability to work directly with l