Quantitative Analytics Associate - Capital
About The Position
Under direct supervision, the Quantitative Analytics Associate is primarily responsible for using statistics, advanced mathematical techniques, and/or computer science to support the development and validation of predictive and machine-learning models for specific business needs. The 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?”. Projects undertaken by the Quantitative Analytics Associate are often broad in scope across multiple business segments and involve evaluation and testing on existing data with substantial team support. This role sits within a specialized economic capital environment and offers the opportunity to work in a highly niche analytical space. The team is actively evolving how work is done by leveraging AI-generated code and modern tools, and this individual will play a key role in accelerating that transition. Success factors include: timely and effective completion of tasks assigned by manager under significant supervision; building functional knowledge in analytical programming languages, data literacy, and model development; developing communication skills, business acumen, and critical thinking; establishing relationships with the working team; demonstrating a self-starter mentality; and contributing to the adoption and advancement of AI-driven solutions across the team.
Requirements
- 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
- Understanding of 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
- Python/R/SAS: Connect to data bases
- Python/R/SAS: Use functions such as classes, variables, lists, and classes
- Python/R/SAS: Program files, modules, and libraries
- 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
- 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
- Understanding of 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
Nice To Haves
- Master’s or PhD
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
Benefits
- Eligibility for incentive compensation which may include production, commission, and/or discretionary incentives.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
