CIFC OVERVIEW
Founded in 2005, CIFC Asset Management LLC (including its affiliates, “CIFC”) is a global credit manager focused across multiple disciplines – CLOs, structured credit, corporate credit, opportunistic credit, and direct lending. Serving institutional investors globally, CIFC is a SEC-registered investment manager with approximately $47 billion in assets under management as of December 31, 2025. For more information, please visit http://www.cifc.com.
Job Overview:
The Structured Credit Analytics Developer will sit alongside CIFC’s structured credit trading desk, partnering directly with traders and portfolio managers to design, build, and maintain the analytical tools that drive trading and investment decisions in CLOs and the broader leveraged loan market. The role combines hands-on software development with applied knowledge of CLOs and structured credit: building data pipelines, pricing and surveillance tools, and bespoke analytics on tight, market-driven timelines. The successful candidate is a self-directed engineer with 3–5 years of programming experience who is comfortable owning workstreams end-to-end, translating ambiguous desk requirements into production-quality tools, and operating at the pace of a live trading floor.
Job Responsibilities
- Design, build, and deploy analytical tools, data pipelines, and surveillance applications that support the structured credit trading desk’s decision-making in CLOs.
- Take desk and portfolio-management requirements from concept through production — including design, implementation, testing, deployment, and documentation — with a focus on reliability and turnaround time.
- Partner directly with traders, portfolio managers, risk, and operations to translate ambiguous business questions into well-scoped technical solutions.
- Own the reliability and evolution of in-production analytics: triage issues against live market data, prioritize against desk impact, and deliver fixes and enhancements without disrupting trading workflows.
- Coordinate with offshore engineering counterparts — setting clear handoffs, reviewing work, and keeping deliverables on track across time zones.
Skills/ Knowledge
- Proficiency in Java, C#, or Python, along with a solid understanding of data structures and multi-threaded distributed programming, is essential for this role.
- Knowledge of SQL / No-SQL database/s, proficient in reading/writing queries and procs.
- Proficiency with a data analysis framework such as pandas/NumPy in Python (or equivalent in Java).
- Ability to come up with creative solutions to find errors and patterns in data.
- Very good analytical and debugging skills for identifying root causes and fixing them in real time.
- Working knowledge of Azure or another major cloud platform (AWS, GCP), including deploying and operating production workloads.
- Good understanding of the latest LLMs (ChatGPT, Claude, Gemini, etc.) and related trends.
- Experience handling multiple requirements at the same time.
- Ability to function at both detail and conceptual levels.
- Strong desk-facing skills — comfortable working directly with traders and portfolio managers, including under time pressure.
- Excellent written and verbal communication skills.
- Familiarity with CLOs or other structured/securitized products (RMBS, CMBS, ABS) is a strong plus.
Characteristics
- Collaborative in the organization and a strong team player. Ability to work autonomously while also integrating appropriately with the team (onsite & offshore).
- Pragmatic in applying technology to solving business issues.
- Good interpersonal skills and the ability to build strong professional relationships at all levels, with both internal and external parties.
- Highly organized, efficient, and able to work under tight deadlines and in a high-pressure environment.
- Composure and resilience when navigating a fast-moving trading floor with direct, results-driven personalities.
- Excellent attention to detail.
- Good planning, organizational, implementation, and follow-up skills required.
Education/ Background
- Bachelor’s degree in computer science, Engineering, Mathematics, Statistics, Financial Engineering, Quantitative Finance, or a related discipline; equivalent experience also considered.
- Master’s degree in any of the above disciplines is a plus.
- 3–5 years of relevant experience.
