KeyCorp

4 weeks ago

Quantitative Analytics Manager - Treasury

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 20 hours agoStatus: Live

Job Summary

Use advanced quantitative methods to build predictive time-series models for CCAR stress testing and corporate forecasts, including pre-provision net revenue (PPNR), interest-rate risk (IRR), asset-liability management (ALM), and liquidity risk. Lead analysis for large, complex problems, review and coach team deliverables, and establish best practices for capturing and retaining data. Communicate technical findings to non-technical partners while improving model and data procedures for efficient delivery.

Location: Cleveland, Chicago, Columbus, Pittsburgh

Workplace: Hybrid

Employment Type: Full time

Job Function: Capital Markets, Trading & Quant

Seniority: Manager level

Key Responsibilities

•Create and leverage models, inferential statistics, and prescriptive analysis to solve business problems and recommend actions.
•Own large, complex analyses with broad implications, less frequent in nature, and recommend solutions based on context and conclusions.
•Review deliverables and proactively coach others on approach and work product.
•Lead and evangelize best practices for capturing and retaining data, coordinate with data stewards, and anticipate process/procedure needs.
•Make continuous improvements to data procedures and model methods, including assessing risks and communicating observations to senior executives and non-technical audiences.

Pay and Benefits

Salary: USD 116,000 - 216,000 annually

Key Requirements

•Master’s degree (or equivalent) in a quantitative field (statistics, mathematics, economics, financial engineering, data science, predictive modeling, etc.) with at least 5 years of relevant experience, or Bachelor’s with at least 6 years of relevant experience.
•Use advanced mathematical/statistical techniques to develop predictive time-series models for CCAR stress testing and corporate forecasting (including PPNR, IRR, ALM, and liquidity risk).
•Proficiency with SQL/NoSQL and experience working with relationship data structures, unstructured data retrieval, archival, and ETL.
•Advanced Python/R/SAS skills, including efficient coding and building strong code controls with clear technical commentary.
•Demonstrated leadership in coaching others, partnering with data/process stakeholders, managing priorities and deadlines, and communicating technical models to non-technical audiences.

Experience:5+ yearsFinancial servicesStress testingPredictive modelingTime-series forecastingAsset-liability management

Skills:LeadershipCommunicationCritical thinkingProblem-solvingCoaching

Tech Stack:Microsoft Office SuiteSQLNoSQLPythonRSASCloud-based computingDistributed computingETLDatabases

Company Brief

KeyCorp

KeyCorp operates KeyBank, providing retail and commercial banking, lending, wealth management, and investment services to individuals, businesses, and institutions across the United States.

Industry: Banking

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Cleveland, United States

Founded: 1849

Glassdoor: 3.6

Website LinkedIn

Loading job details...

Preparing the role view and application actions.

KeyCorp

4 weeks ago

Quantitative Analytics Manager - Treasury

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 20 hours agoStatus: Live

Job Summary

Location: Cleveland, Chicago, Columbus, Pittsburgh

Workplace: Hybrid

Employment Type: Full time

Job Function: Capital Markets, Trading & Quant

Seniority: Manager level

Key Responsibilities

•Create and leverage models, inferential statistics, and prescriptive analysis to solve business problems and recommend actions.
•Own large, complex analyses with broad implications, less frequent in nature, and recommend solutions based on context and conclusions.
•Review deliverables and proactively coach others on approach and work product.
•Lead and evangelize best practices for capturing and retaining data, coordinate with data stewards, and anticipate process/procedure needs.
•Make continuous improvements to data procedures and model methods, including assessing risks and communicating observations to senior executives and non-technical audiences.

Pay and Benefits

Salary: USD 116,000 - 216,000 annually

Key Requirements

•Master’s degree (or equivalent) in a quantitative field (statistics, mathematics, economics, financial engineering, data science, predictive modeling, etc.) with at least 5 years of relevant experience, or Bachelor’s with at least 6 years of relevant experience.
•Use advanced mathematical/statistical techniques to develop predictive time-series models for CCAR stress testing and corporate forecasting (including PPNR, IRR, ALM, and liquidity risk).
•Proficiency with SQL/NoSQL and experience working with relationship data structures, unstructured data retrieval, archival, and ETL.
•Advanced Python/R/SAS skills, including efficient coding and building strong code controls with clear technical commentary.
•Demonstrated leadership in coaching others, partnering with data/process stakeholders, managing priorities and deadlines, and communicating technical models to non-technical audiences.

Experience:5+ yearsFinancial servicesStress testingPredictive modelingTime-series forecastingAsset-liability management

Skills:LeadershipCommunicationCritical thinkingProblem-solvingCoaching

Tech Stack:Microsoft Office SuiteSQLNoSQLPythonRSASCloud-based computingDistributed computingETLDatabases

Company Brief

KeyCorp

KeyCorp operates KeyBank, providing retail and commercial banking, lending, wealth management, and investment services to individuals, businesses, and institutions across the United States.

Industry: Banking

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Cleveland, United States

Founded: 1849

Glassdoor: 3.6

Website LinkedIn