Quantitative Analytics Associate

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)
• Test, 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
• At least 1 year of relevant experience; 0 with Master’s or PhD

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 databases
  • 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

Compensation

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 may include production, commission, and/or discretionary incentives.