Quant Analytics Sr Assoc
About The Position
The Senior Quantitative Analytics Associate uses statistics, advanced mathematical techniques, and/or computer science to develop and validate predictive and machine-learning models for business needs. The role applies advanced mathematical knowledge and analysis to answer predictive and prescriptive questions, often through projects spanning multiple business segments and involving model development or maintenance. The associate connects analyses and conclusions with partner needs and business strategy. The role designs advanced modeling approaches and modifies existing models in response to changing business needs, trends, and strategy. It applies analytical programming, data literacy, and model-development skills to deliver predictive analyses that inform business problems. The associate leads conversations with business partners, translates complex concepts into accessible language, and serves as an emerging leader and role model across the team. The position is based at 4910 Tiedeman Road, Brooklyn, Ohio. Key prioritizes in-office presence while providing flexible options when roles can be performed effectively in a mobile environment. The role is eligible for a base salary of $96,000–$181,000 annually, with eligibility for incentive compensation that may include production, commission, and/or discretionary incentives. Benefits eligibility is referenced, but specific benefits are not listed.
Requirements
- Master’s degree or equivalent in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling, or another quantitative discipline, plus at least 3 years of relevant experience; or a bachelor’s degree or equivalent in one of these disciplines, plus at least 5 years of relevant experience.
- Working knowledge of different types of data and techniques for managing data structures.
- Ability to link conclusions from data analysis to business impacts.
- Advanced Microsoft Office Suite skills.
- Knowledge of SQL/NoSQL, relational data structures, databases, and selecting and retrieving data, including unstructured-data retrieval, archival, and ETL.
- Advanced Python, R, or SAS skills, including efficient coding, strong code controls, and translating code into high-level commentary.
- Understanding of and ability to leverage cloud-based and distributed computing.
- Knowledge of optimization techniques and numerical-analysis requirements for algorithms and models.
- Ability to assess model performance and assumption reliability, identify when to escalate, and determine model requirements from business processes.
- Strong relationship-building, interpersonal, partnering, and influencing skills; ability to lead conversations with business and technology partners.
- Understanding of assigned line-of-business strategy, competitors, industry, financial-result drivers, and business impact.
- Strong critical-thinking and problem-solving skills, including assessing cross-functional impacts, potential pitfalls, and alternative solutions.
- Strong writing and presentation skills, including organizing material for clarity and impact and communicating appropriately detailed information to stakeholders.
- Ability to share relevant information proactively and communicate effectively in situations involving conflict.
Responsibilities
- Use critical thinking to develop insights and predictive analyses that answer business questions about what may happen next.
- Develop, design, and leverage advanced modeling approaches, standard data-inference and performance techniques, algorithms, and models.
- Identify and anticipate business needs and obtain the appropriate information.
- Communicate predictive insights to partners, using past trends to anticipate future behavior and linking analytical conclusions to business impact.
- Navigate the model approval process as needed.
- Suggest process improvements.
- Serve as an emerging team leader and role model; contribute to junior staff’s work products and help others develop, publish, and customize models.
- Identify and apply best practices.
- Guide information retention, coordinate with data stewards, and anticipate process and procedure needs.
- Define processes for integrating and repurposing data analyses.
- Interpret model performance and the reliability of assumptions, and identify when escalation is needed.
- Lead the design of advanced modeling approaches and develop standard techniques for data inference and performance.
- Determine model use requirements based on business processes and apply best practices during implementation.
- Build relationships and influence business and technology partners; communicate analyses and recommendations effectively to stakeholders.
Benefits
- Eligible for incentive compensation, which may include production, commission, and/or discretionary incentives.
- Benefits eligibility is indicated; specific benefits are not listed in the posting.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
