Quant Analytics Assoc.

Location: 4900 Tiedeman Road, Brooklyn Ohio

About the role

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. 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; and establishing relationships with the working team.

Responsibilities

• Conduct quantitative analysis on large data sets with manager and team support
• Identify common data errors and their impact
• Employ basic best practices for evaluating large data
• Answer key business questions through exploration and discovery
• 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)

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.

Skills

Data Literacy

• 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

Technology & Techniques

• Advanced Microsoft Office Suite
• 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

Model Building & Maintenance

• 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

Expected Competencies

• Leadership: Works under general direction / supervision; may work independently, but often needs ongoing guidance and support
• Partnering / Influencing: 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
• Business Acumen: Developing basic understanding of business partner strategy; Building financial acumen
• Critical Thinking / Problem Solving: 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
• Communication: 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

Pay

This position is eligible to earn a base salary in the range of $69,000.00 - $105,000.00 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