Quant Analytics Lead Associate- Market Risk Model Validation

KeyBank • Cleveland, OH

3d • $71,000 - $125,000 • Remote

About The Position

Under some supervision, the Lead Quantitative Analytics Associate is primarily responsible for using statistics, advanced mathematical techniques, and/or computer science to validate predictive and machine-learning models for specific business needs. The Lead Quantitative Analytics Associate leverages advanced mathematical knowledge and analysis to provide solutions to predictive and prescriptive questions such as “What will happen next?” and “What will we do?”. Often large in scope, projects undertaken by the Lead Quantitative Analytics Associate involve self-directed data analysis and model validation in response to a problem statement proposed by a business partner. Success factors include timely and effective completion of tasks assigned by manager with manager and/or peer guidance; exercising functional knowledge in analytical programming languages, data literacy, and model validation; effective communication of insights and data to peers; and developing work autonomy and problem-solving. Role focus (Market Risk – Banking Book & Trading Book): This role supports market risk model validation across the banking book and trading book. This includes Interest Rate Risk in the Banking Book (IRRBB) measurement, balance sheet and net interest income (NII) modeling, behavioral modeling for non-maturity deposits (NMD), trading book valuation/pricing for derivatives, etc.

Requirements

• Bachelor’s degree (or its equivalent) in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling, or other quantitative disciplines and at least 2 years of relevant experience; 1 with master’s or PhD
• DATA LITERACY Understanding of and ability to: Create data structures / transformations Identify and capture different types of information for business needs or necessary for analysis Data controls Hypothesis testing / root-cause analysis Leverage and anticipate considerations in implementation
• TECHNOLOGY & TECHNIQUES Advanced Microsoft Office Suite SQL/NoSQL Relationship data structure Selecting and retrieving data including unstructured data retrieval, archival, and ETL Databases Familiarity with balance sheet/ALM modeling platforms (e.g., QRM) and associated data inputs/assumptions for IRRBB and NII/EVE analytics Trading book analytics and derivatives valuation (e.g., Calypso) with independent price verification and market data familiarity (e.g., Bloomberg) Advanced Python/R/SAS (including building internally developed behavioral models such as deposit attrition/decay, strong code controls, and translating code into clear documentation and commentary): Databases Efficient coding Can build strong code controls and translate code into high-level commentary Understanding of and ability to leverage: Cloud-based computing Distributed computing
• MODEL VALIDATION & MAINTENANCE Understanding of: Model use, requirements, and implementation needs Market risk model contexts and governance, including IRRBB requirements (e.g., EVE/NII measurement, key rate shocks/scenarios, behavioral assumptions for NMDs), as well as trading book valuation controls (e.g., model inputs, market data, IPV/valuation adjustments) Model Risk Management process and foundations Testing for deterioration and model health Scale and fundamental concepts of Machine Learning How statistical measurements are used Advanced data techniques for modeling frameworks Ability to: Produce and identify information through statistical analysis Effectively explain model insights to peers and analytics community Identify preferred approach given the problem statement
• EXPECTED COMPETENCIES Leadership: Some self-direction, likely will need some guidance and supervision; Starting to anticipate possible business problems – improving something that already exists Partnering / Influencing: Developing relationship building and interpersonal skills; Partnerships and influence typically at peer or “working group” level; Building influencing skills; demonstrated in area of expertise or assigned LOB Business Acumen: Understands business partner strategy and the business of banking at a high level; Asks the right questions; Understands upstream and downstream impacts Critical Thinking / Problem Solving: Demonstrates critical thinking; Analyzes, identifies and recommends appropriate solutions to moderately complex problems; Can translate data and answer the “why” question; Starting to understand impacts / intersections with others Communication: Solid writing skills; Can cohesively present and organize information in support of findings and recommendations; Demonstrates confidence in communicating a message (typically narrow in scope); Can tell a compelling story with data and information; Emerging presentation development and delivery skills

Responsibilities

• Conduct quantitative analysis to support market risk model validation across banking book (IRRBB) and trading book.
• Partner with stakeholders to define data and information requirements for IRRBB, balance sheet/ALM, and trading book analytics; create and maintain data structures, transformations, and controls to enable repeatable analysis and reporting.
• Validate quantitative models used for market risk and valuation, including IRRBB metrics (e.g., EVE/NII sensitivities), balance sheet projections (e.g., using QRM), behavioral models (e.g., deposit attrition/decay implemented internally in Python), and trading book derivatives pricing/valuation models (e.g., Calypso outputs benchmarked to Bloomberg and other independent sources).
• Apply critical thinking to select fit-for-purpose methodologies for market risk use cases (banking book vs. trading book), including sensitivity and scenario design, back-testing/benchmarking strategies, and assessment of limitations and compensating controls.
• Anticipate business and regulatory needs (including IRRBB and Market Risk Rule expectations) and drive continuous improvements to validation routines for balance sheet risk and trading book valuation.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees