PostMatches By WorkStaff USA

Quantitative Services (QS) team is the business owner for several key processes like UMR IM explain and dispute, SEC rule alignment and Risk Optimization. QS will be responsible for providing no harm and assessing IM impacted on regulatory IM calculation in compliance with SEC final rules. Assisting CPM desk and other FO teams on IM attribution analysis, what-if scenarios and VM prediction.

Assist FO desk on IM impact and driven risk factor analysis. enhance IM attribution report and support Collateral and Liquidity impact analysis.
Run unit testing and impact analysis on SIMM model annual back testing and implementation.
Apply mathematical or statistical techniques to address practical issues in UMR program, such as SIMM IM calculation and monitoring, risk management, CSA transition and other regulatory requirements.
Understand quantitative libs and their usage to assist FO/Risk pricing, what-if scenario on IM calculation and Capital RWA impact;
Assess IM impact under Uncleared Margin Rules (UMR). Verify the model inputs (e.g. market data) and the calculations. Ensure the firm’s IM calculations are accurate. Identify and establish control processes that will mitigate future IA calculation errors.
Work directly with front office, business support and technology teams to enhance risk optimization approach. Provide analysis to various stakeholders.

Required Skills: (Must have these skills to be minimally qualified)

2+ years of experience working in a quantitative risk, middle office, or front office role
Python programming, SQL, VBA experience
Knowledge of broad range of OTC derivative, FIF, Repo and loan products, Credit Risk, VaR and XVA Models for FO or Risk valuation.
Ability to leverage strong quantitative and programming skills to build deep knowledge of the bank’s analytical libraries and infrastructure
Experience with handling large data set with the ability to transform information into concise presentations with sound business conclusions and recommendations
Strong analytical and problem solving skills with the ability to interpret large amounts of information and conceptualize the impact across operational processes
Excellent communication & analytical skills
Master degree or higher in Computer Science, Mathematics, Financial Engineering, Economics or related quantitative field


Strives to bring new thoughts and ideas to teams in order to drive innovation and unique solutions.
Excels in working among diverse viewpoints to determine the best path forward.
Experience in connecting with a diverse set of clients to understand future business needs – is a continuous learner.
Commitment to challenging the status quo and promoting positive change.
Participate in and drive collaborative efforts to advance tools, technology, and ways of working to better serve an evolving client base.
Believes in value of diversity so we can reflect, connect and meet the diverse needs of our clients and employees around the world.

Enterprise Role Overview:

Leads multiple projects that are significant in scope and impact.

Serve as a SME and use that expertise to influence the optimal design and delivery of projects.

Expected to lead by influence and drive strategic adoption.

Demonstrated progressive growth in skill and responsibilities in various roles.

Has extensive professional and functional knowledge developed through financial industry experience.

Key responsibilities include:

Provide subject matter expertise in process design, tool development or methodology validation

Design and roll out analytical and technical tools for validations of new models/methodology

Provides guidance and mentoring to junior analysts as needed

Be a solution provider who can leverage the knowledge and experience to deliver a high quality end product; and Understands financial products across all asset classes and has extensive knowledge of technical implementations. Posses advanced degree in physic, applied mathematics, statistics/probability or another heavy quantitative discipline.


Please Login/Sign Up to Apply!