[Remote] Quantitative Analytics Associate - Capital

Note: The job is a remote job and is open to candidates in USA. KeyBank is a financial services company seeking a Quantitative Analytics Associate to support the development and validation of predictive and machine-learning models. The role involves conducting quantitative analysis, identifying data errors, and contributing to the integration of AI tools into workflows while working under supervision.

Responsibilities

• Conduct quantitative analysis on large data sets with manager and team support, including work tied to economic capital modeling frameworks
• Identify common data errors and their impact
• Employ basic best practices for evaluating large data
• Answer key business questions through exploration and discovery, including those tied to risk and capital modeling
• Find patterns or anomalies by building out visualizations
• Execute basic diagnostics testing under supervision (e.g. performance testing, assumption verification and impacts of limitations)
• Tests, under supervision, suitability / sufficiency for approach (e.g. representativeness)
• Support the team’s transition toward AI-generated code, helping integrate AI tools into day-to-day workflows
• Partner with team members to increase adoption and effective use of AI platforms and agentic tools
• Learn existing economic capital approaches and help identify opportunities to enhance processes through automation and AI-driven solutions

Skills

• Bachelor's degree (or its equivalent) in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling, or other quantitative disciplines and at least 1 year of relevant experience; 0 with Master's or PhD
• Understanding of data wrangling including information documentation and importing data from different formats
• Descriptive statistics, random variables, common distributions, outliers
• Ability to consume, explore, and evaluate big data; can leverage this skill to inform business questions
• Baseline understanding or interest in economic capital modeling concepts or similar quantitative frameworks
• Navigation, shortcuts, use and share spreadsheet documents
• Python/R/SAS: Perform IDE walk-through; shortcuts
• Connect to data bases
• Use functions such as classes, variables, lists, and classes
• Program files, modules, and libraries
• Familiar with concepts and usage of Data Leakage, Training, Testing, and Validation Sets for model building
• Able to perform basic diagnostics testing
• Understanding of foundational statistical / measurement concepts, methods, and techniques
• Basic uses, scope, features, benefits, and risks of available modeling methods
• Ability to apply these concepts within an economic capital or risk modeling context over time
• Works under general direction / supervision; may work independently, but often needs ongoing guidance and support; demonstrates initiative and ownership in a self-starter environment
• Limited business partner interaction – work typically assigned by manager; Developing relationship building ability and interpersonal skills; Engage and interact mostly with immediate team and peers; Developing influencing skills; supports team adoption of new tools and approaches, including AI
• Developing basic understanding of business partner strategy; Building financial acumen; gains exposure to economic capital concepts and their business relevance
• Developing critical thinking skills; Can analyze simple issues with low complexity; Can give perspective to the team addressing basic business/analytical problems and challenges; Recognizes need to escalate issues in a timely manner; demonstrates curiosity and problem-solving mindset around process improvement and automation
• Basic writing skills; beginning to develop ability to organize information in clear, consistent format; Typically needs assistance with articulating a clear, well-thought out message and formal delivery; Minimal skills in creating PowerPoint presentations; limited formal delivery; able to collaborate effectively and is easy to work with
• Exposure to or interest in standard AI and machine learning tools, including generative AI platforms
• Familiarity with or curiosity around agentic tools and AI-assisted coding environments

Benefits

• Eligibility for incentive compensation which may include production, commission, and/or discretionary incentives.
• 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.

Company Overview