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Lead Quantitative Analytics Associate II - Business Banking & Consumer AnalyticsKey Bank • United States
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Lead Quantitative Analytics Associate II - Business Banking & Consumer Analytics

Key Bank
  • US
    United States
  • US
    United States
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Über

Location: 4900 Tiedeman Road, Brooklyn Ohio ABOUT THE JOB (JOB BRIEF) Under some supervision, the Lead Quantitative Analytics Associate is primarily responsible for using statistics, advanced mathematical techniques, and/or computer science to develop and 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 building 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 development; effective communication of insights and data to peers; and developing work autonomy and problem-solving. ESSENTIAL JOB FUNCTIONS
Use traditional statistical methods and machine learning to develop, monitor, maintain, and implement models that address the right business need including CECL, Stress Testing, Account Management, Origination Scorecard and Macroeconomic Forecast Assess and challenge data preparation practices against established standards and model requirements, engage with data stewards to review data quality, traceability, and efficiency from a validation perspective Often responsible for large, complex problems that have broad implications and are less frequent Identify and articulate observations based on a structured assessment of context, interdependencies, and analytical outcomes, and evaluate their impact on model soundness, reliability, and business use Reviews deliverables; proactively coaches others on approach and work product Evaluate the appropriateness of analytical methods used and assess whether they are suitable and well justified for the given context REQUIRED QUALIFICATIONS
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 Traditional (e.g. Linear Regression, Logistic Regression) with the ability to design and optimize modeling evaluate, challenge, and validate model design, and performance testing Intermediate Python/SQL:
Write and Read functions (Py) and Windows function (SQL) Understand Data Import and Joins Can build code controls and translate code into commentary
Advanced modeling techniques, including machine learning methods (e.g., XGBoost, LightGBM, Random Forest), with the ability to design and optimize modeling evaluate, challenge, and validate model design, and performance testing Git
Can build strong code controls Resolve Conflict Work Collaboratively contributing to one Codebase
Advanced Python/SQL:
Write and Read Class and Unite Test Write and Read Advanced Windows functions Can build strong code controls and translate code into high-level commentary
Understanding of and ability to leverage:
Cloud-based computing Distributed computing
Agentic AI (LLM, MCP, RAG) MODEL BUILDING & MAINTENANCE
Understanding of:
Model use, requirements, and implementation needs Testing for deterioration and model health fundamental concepts of Machine Learning How statistical measurements are used
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 Understanding of:
Model Risk Management process and foundations Scale concepts of Machine Learning
Advanced data techniques for modeling frameworks 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 COMPENSATION AND BENEFITS This position is eligible to earn a base salary in the range of $71,000.00 - $125,000.00 annually. Placement within the pay range may differ based upon various factors, including but not limited to skills, experience and geographic location. Compensation for this role also includes eligibility for incentive compensation which may include production, commission, and/or discretionary incentives.
Please click here for a list of benefits for which this position is eligible. Key has implemented an approach to employee workspaces which prioritizes in-office presence, while providing flexible options in circumstances where roles can be performed effectively in a mobile environment. Job Posting Expiration Date: 07/06/2026
KeyCorp is an Equal Opportunity Employer committed to sustaining an inclusive culture. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, genetic information, pregnancy, disability, veteran status or any other characteristic protected by law.
Qualified individuals with disabilities or disabled veterans who are unable or limited in their ability to apply on this site may request reasonable accommodations by emailing HR_Compliance@keybank.com. #LI-Remote
  • United States

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  • English
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