Associate Principal, Quantitative Risk Management

OCC • Chicago, IL

4d • $111,100 - $199,900 • Hybrid

About The Position

The Associate Principal is responsible for one or more functions within Quantitative Risk Management (QRM) to develop and maintain model performance monitoring. The Senior Associate will collaborate with other quantitative analysts, business users, data & technology staff, and model validation colleagues to implement new analytics and enhance existing tools.

Requirements

• Strong programing skills. Able to read and/or write Python code in a collaborative software development setting.
• Experience with a source code repository system (preferably Git)
• Ability to write and optimize complex analytical (SELECT) SQL queries
• Ability to collaborate with multiple partners (e.g., DBAs, Data Architecture, Security) to craft solutions that align business goals with internal security and development standards
• Comfortable supporting business analysts on high-priority projects.
• High attention to detail and ability to think structurally about a solution
• Strong problem-solving skills: Be able to accurately identify a problem's source, severity, and impact to determine possible solutions and needed resources.
• Experience in a scripting language such as Python is required.
• Experience in office technology such as PowerPoint, Confluence, Jira, Word, and Excel.
• Experience with code repository, build and deployment tools (e.g., Git, GitHub, Jenkins).
• Proficiency in database technology and query languages (such as SQL).
• Master’s degree or equivalent in a quantitative field such as data analytics, computer science, mathematics, physics, finance/financial engineering.
• 2 years of experience in data analytics required

Nice To Haves

• Exposure to data orchestration tools, such as Airflow
• Understanding of applied statistics and hands-on experience applying these concepts
• Strong quantitative skills, ability to demonstrate deep understanding in the following technical areas: Financial mathematics (derivatives pricing models, stochastic calculus, statistics and probability theory, advanced linear algebra), Econometrics, data analysis (e.g., time series analysis, GARCH, fat-tailed distributions, copula, etc.) and machine learning techniques, Numerical methods and optimization; Monte Carlo simulation and finite difference techniques, Risk management methods (value-at-risk, expected shortfall, stress testing, backtesting, scenario analysis)
• Financial products knowledge: good understanding of markets and financial derivatives in equities, interest rate, and commodity products.
• Model development and prototyping require advanced development skills in Python and database manipulation.
• Ability to challenge model methodologies, model assumptions, and validation approach.
• Proficiency in technical and scientific documentation (e.g., white papers, user guides, etc.).
• Experience with Tableau, Dash and Alteryx
• Experience with numerical libraries and/or scientific computing is preferred.
• Experience with automated quality assurance frameworks for model testing is preferred.
• Software design: effective application of design patterns, expertise in object-oriented design
• Experience with high performance computing is a plus.
• Non-relational DB and other Big Data, cloud-based computing experience is a plus.
• Experience in areas in finance and/or development experience in model implementation and testing.
• FRM, CFA, etc., are desirable, but not required.

Responsibilities

• Maintain and build data models to ensure information is available in our analytics warehouse for downstream uses, such as analysis and dashboard development
• Perform model performance monitoring implementation and testing, including portfolio back-testing using historical data.
• Review implementation of model monitoring metrics and algorithms focusing on requirement verification, coding, and testing quality.
• Write and review documentations for model monitoring metrics, prototypes and implementation.
• Support the launch of new products by enhancing monitoring capabilities.
• Create documentation and testing to ensure data is accurate and easily understandable
• Discover and share best practices for data and analytics engineering with members of the team
• Invest in your continued learning on data and analytics engineering best practices and evaluate them for fit in improving maintainability and reliability of analytics infrastructure
• Develop Python scripts with Pandas and object-oriented programming to automate data processing
• Conduct visualization and exploratory analysis using advanced statistical methods
• Participate in model performance monitoring code reviews and troubleshooting
• Assist analysts in solving their analytics questions/challenges

Benefits

• A hybrid work environment, up to 2 days per week of remote work
• Tuition Reimbursement to support your continued education
• Student Loan Repayment Assistance
• Technology Stipend allowing you to use the device of your choice to connect to our network while working remotely
• Generous PTO and Parental leave
• 401k Employer Match
• Competitive health benefits including medical, dental and vision

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level