Principal

Blue Owl Capital•Greenwich, CT

3d•$200,000 - $250,000•Hybrid

About The Position

Blue Owl (NYSE: OWL) is a leading asset manager that is redefining alternatives®. With over $315 billion in assets under management as of March 31, 2026, we invest across three multi-strategy platforms: Credit, Real Assets and GP Strategic Capital. Anchored by a strong permanent capital base, we provide businesses with private capital solutions to drive long-term growth and offer institutional investors, individual investors, and insurance companies differentiated alternative investment opportunities that aim to deliver strong performance, risk-adjusted returns, and capital preservation. Together with over 1,390 experienced professionals globally, Blue Owl brings the vision and discipline to create the exceptional. To learn more, visit www.blueowl.com This role is in office Monday to Thursday. The Role We are seeking a high-output “athlete” to sit at the intersection of portfolio management, trading, and structured credit, owning analytics and tooling that improve portfolio construction, monitoring, and trade decision-making across our CLO platform. This person will build and automate Excel- and dashboard-based analytics, data-mine large datasets, run hypothetical trade and test analysis, and support relative value / peer comparisons vs other managers and vehicles.

Requirements

7+ years of total professional experience within structured finance, credit, or related fields.
3-7 years of direct CLO experience, ideally in a collateral manager, trustee, auditor, middle office, ratings, structuring/trading support, or valuation seat.
Strong understanding of CLO structures and portfolio test mechanics; ability to interpret governing docs and translate into a model/checklist.
Advanced Microsoft Excel: large dataset manipulation, modeling, automation (Power Query/Power Pivot preferred; VBA helpful).
Utilized AI tools (e.g., Claude) to aggregate and analyze unstructured data, supporting portfolio construction, stress testing, and ongoing risk surveillance.
Experience leveraging AI tools (including Anthropic’s Claude) to synthesize large datasets, automate research workflows, and enhance decision‑making.
Proven experience producing portfolio reporting (weekly/monthly/quarterly) and reconciling trustee / system outputs.
Strong written/verbal communication—can synthesize complex trade/test impacts into clear “so what” recommendations.
Hands-on with common CLO / loan / cashflow tooling (Intex, CDO Suite/Solvas, WSO, Nexus, Bloomberg data extraction).
SQL and/or Python for data processing, automation, and repeatable analytics.
BI/dashboard experience (e.g., Power BI) and ability to publish executive-ready views and self-serve analytics.
Experience building internal tools/reports specifically to facilitate daily monitoring, optimizations, and hypothetical tests in partnership with PMs/traders.

Responsibilities

Produce and maintain daily/weekly portfolio snapshots, dashboards, and KPI packs for PMs/traders (exposures, concentrations, collateral quality, tests, price/rating moves, watchlist signals).
Reconcile inputs across trustee reports, internal systems, and market data; ensure data integrity and “one version of truth.”
Track CLO compliance tests and structural triggers; proactively flag potential issues before they become binding constraints.
Run pro-forma / hypothetical trade analysis and communicate impacts on OC/IC tests, WARF/WAS/WARF cushion, concentrations, CCC buckets, and other indenture constraints.
Partner with PMs and trading to propose optimization ideas (relative value, risk reduction, par build, liquidity management).
Support new issue, reset, refi, and warehouse ramp processes with reporting/tie-outs and trade testing.
Build, enhance, and automate Excel-based portfolio tools (Power Query, Pivot/Power Pivot, advanced formulas, VBA where helpful) and/or integrate with BI dashboards.
Design repeatable workflows for ingesting, cleaning, and mapping large datasets (loan terms, ratings, pricing, exposures, test data) and reducing manual steps.
Create benchmarking views to compare portfolios vs peer managers/vehicles (risk posture, quality metrics, concentrations, tail risk, trading cadence, performance drivers) and respond to ad hoc investor and internal questions quickly with data.
Act as a connective hub across PMs, trading, operations/middle office, legal/structuring, and tech/data teams to ensure analytics are accurate, scalable, and decision-useful.