Co-op, Quantitative Research

Job Description:

Description

We are looking for Quantitative Researcher to join our Counterparty -Risk and Analytics group. We are a collaborative, data-driven, intellectually rigorous team responsible for the identification, measurement, monitoring and analysis of the counterparty credit risk and contingent risk matters related to Fidelity's trading partners. We maintain a team-oriented environment and place a high value on professionalism, attitude, and initiative.

Responsibilities

CRA Quant team is focused on developing and implementing risk exposure analytics framework. These include models related to Probability of Default using Machine Learning and AI, PFE modeling, Securities Pricing, Value-at-Risk, Stress Testing and also, developing visualization tools to gain analytical insight into the creditworthiness of our counterparty universe. The ideal candidate will work closely with Quant Team members to develop and enhance risk models to ensure risks are appropriately captured. Responsibilities include but are not limited to:

• Work on new predictive models based on large fundamental and market-based financial data sets, using time-series modeling, ML, and statistical and data science techniques in the financial industry
• Utilize advanced mathematical and quantitative skills including derivative pricing and stochastic simulations to assist in development and enhancement of PFE modeling of derivative products
• Source, curate and visualize data sets, perform ad-hoc analysis on wide varieties of risk analytic projects aimed at efficiently identifying stressed counterparties
• Collaborate with business partners (technologists, research analysts, and our internal risk monitoring team) to analyze existing capabilities and room for improvement in visualizing/presenting data to stakeholders. Lead the initiative of redesigning counterparty risk dashboards, and generate charts and graphs to deliver an actionable story to the stakeholders
• Present and communicate results and ideas of projects clearly and concisely to CRA team members and stakeholders as needed.

Qualifications

• Enrolled in graduate program in finance, mathematics, economics, or a closely-related discipline emphasizing quantitative and financial analysis
• Strong analytical, quantitative, and problem solving skills
• Understanding of probability, statistics, linear regression, time-series analysis, linear algebra, and calculus
• Knowledge of the application of statistics to economics (including econometrics or regression analysis)
• Hands on experience in developing or validating statistical/mathematical models. Strong attention to detail with the ability to synthesize multiple sources of information
• Experience managing and manipulating large data sets and extracting useful insights and visuals
• Strong programming skills in Python. SQL knowledge a bonus
• Familiarity with financial data products
• Experience with AI/Machine Learning techniques preferred
• Passion for financial markets
• Strong communication skills, both written and verbal and a proven ability to build relationships and work as part of a team.
• High energy and strong work ethic

Certifications:

Category:

Administration