- Evaluate the accuracy of the end-to-end process that is executed daily to generate various measures of market risk exposure for a portfolio of financial instruments. Evaluate that accuracy for the individual components that this process relies on (data systems, analytics systems and models implemented in those analytical systems), and the accuracy of the integration between those components.
- Evaluate third-party economic driver models, financial instrument cash flow models, analytical systems and data systems to understand the differences between proprietary and third-party models/systems.
- Apply advanced skill, knowledge, and/or experience in translating complex business requirements into new proprietary modeling requirements for both economic driver models and financial instrument cash flow models, and into new implementation requirements for the analytics systems that rely on those models to generate measures of market risk exposure for a portfolio of financial instruments.
- Generate user acceptance test analysis results before proposed enhancements to the portfolio market risk exposure measurement process are adopted, to ensure they meet business needs. Make recommendation to business users on whether to adopt or not to adopt such enhancements.
- 4 years
- Bachelor's degree with 6 years or Master's degree with 4 years or equivalent experience in quantitative sciences such as Physics, Applied Mathematics, Statistics, Economics, Finance, Computer Science, Engineering
- Experience working as a Lead Analyst
- Experience working with various stakeholders across Finance, Capital Markets and other lines of business
- Experience developing solutions to customer needs and having trade-off discussions with customers
- Proactive, creative problem solver with strong analytical skills. Must be able to define problem space as well as potential solutions
- Demonstrated strong analytical and problem-solving skills to conduct analysis independently to address complex economic or business problems
- Experience working with financial data, analytics and cashflows applications
- Experience interpreting the results of econometric modeling and statistical analysis
- Programming experience in coding and debugging custom SAS or Python scripts used for ad-hoc analysis of large datasets
- Proficiency in Unix/Linux environment
- Proficiency in SQL, relational and noSQL databases, query optimization and data modeling
- Embraces new technologies, enjoys finding opportunities for making existing systems and processes more efficient and seizing those opportunities
- Skilled in the graphical representation of information in the form of a charts, diagrams, pictures, and dashboards with programs and tools such as Excel, MicroStrategy, Tableau
- Experience gathering accurate information to explain concepts and answer critical questions
- Skilled in documentation and database querying for the purposes of analysis and data discovery, with the use of relevant software such as Excel and SQL
- Ability to frame ideas as systems and analyzing the inputs, outputs, and process
- Expertise in using statistical methods, including: developing and testing hypotheses, using experimental design
- Experience in the process of analyzing data to identify trends or relationships to inform conclusions about the data
- Skilled in presenting information and/or ideas to an audience in a way that is engaging and easy to understand
- Skilled in Influencing including negotiating, persuading others, facilitating meetings, and resolving conflict
- Adept at managing project plans, resources, and people to ensure successful project completion
- Working with people with different functional expertise respectfully and cooperatively to work toward a common goal
- Business Insight including advising, designing business models, interpreting customer and market insights, forecasting, benchmarking, etc
- Experience identifying measures, or indicators of system performance, and the actions needed to improve or correct performance to achieve desired outcomes
- Skilled in Excel
- Skilled in MicroStrategy or Tableau
- Skilled in Python object-oriented programming
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Lead Quantitative Financial Engineer - Washington, United States - Fannie Mae
Description
Company Description
At Fannie Mae, futures are made. The inspiring work we do helps make a home a possibility for millions of homeowners and renters. Every day offers compelling opportunities to impact the future of the housing industry while being part of an inclusive team thriving in an energizing, flexible environment. Here, you will grow your career and help create access to fair, affordable housing finance.
Job Description
As a valued colleague on our team, you will act as team lead for the evaluation of the reasonableness for all components of financial models, cash flow simulations, P&L, and risk metrics calculations in end-user or production computing systems for use in business decisions, financial and regulatory reporting, and risk management, as well as coach and mentor team members.
THE IMPACT YOU WILL MAKE
The Lead Quantitative Financial Engineer role will offer you the flexibility to make each day your own, while working alongside people who care so that you can deliver on the following responsibilities:
Qualifications
THE EXPERIENCE YOU BRING TO THE TEAM
Minimum Required Experiences
Desired Experiences
Skills
Tools
Additional Information
The hiring range for this role is set forth on each of our job postings located on Fannie Mae's Career Site. Final salaries will generally vary within that range based on factors that include but are not limited to, skill set, depth of experience, certifications, and other relevant qualifications. This position is eligible to participate in a Fannie Mae incentive program (subject to the terms of the program). As part of our comprehensive benefits package, Fannie Mae offers a broad range of Health, Life, Voluntary Lifestyle, and other benefits and perks that enhance an employee's physical, mental, emotional, and financial well-being. See more