Fixed Income Product Manager
Cantor Fitzgerald
United States
5 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source
Tech stack
Microsoft Excel
Data Analysis
Confluence
JIRA
Automation of Tests
Databases
Python (Programming Language)
NoSQL
Oracle (Applications)
Standard Sql
Software Requirements Analysis
Jupyter Notebook
+3 more
Sybase
Pandas
Matplotlib
Job description
The Fixed Income Product Manager will act as the bridge between business stakeholders, broking desks, and technology teams. The successful candidate will help identify, define, and deliver platform enhancements that drive revenue growth, expand market coverage, and ensure regulatory compliance., * Collaborate with business stakeholders to identify new feature opportunities that enhance revenue potential, market reach, and compliance.
- Translate business requirements into clear, actionable system requirements.
- Liaise between broking desks, developers, and QA teams to ensure successful implementation and rollout of solutions.
- Support QA during testing and coordinate User Acceptance Testing (UAT) with end users to ensure timely sign-offs.
Requirements
- Deep understanding of Fixed Income products including Treasuries, Gilts, EGBs, TIPS/Linkers, and Corporate Bonds.
- Strong grasp of derivative instruments such as Credit Default Swaps (CDS) and Interest Rate Swaps (IRS), OIS, FRAs, Caps/Floors, and Swaptions.
- Excellent understanding of price, yield-to-maturity, and DV01 concepts and their underlying calculations.
- Familiarity with structured trades and packages (switches, flies, basis, gadgets, spread switches) and how they are priced and settled.
- Knowledge of trading protocols such as Central Limit Order Books (CLOB) and auction mechanisms.
- (Optional) Understanding of implied trading and legging strategies.
Technical Skills
- Advanced Excel proficiency.
- Working knowledge of SQL for querying databases (Oracle, Sybase, NoSQL).
- Ability to conduct data analysis in Python using frameworks such as Pandas and Matplotlib (in Jupyter Notebook or Google Colab).
- Ability capture requirements in Confluence and Jira
- Familiarity with test automation and ability to guide the QA team on test scenarios
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