Data Mining Associate

In this position, the practitioner will use advanced statistical/predictive modeling, trend analysis, and other data analysis techniques to identify anomalies, patterns, and behaviors from disparate data sets to support key strategic business decisions.


Specific Duties and Responsibilities:

  • Design and develop leading–edge statistical/predictive models from multiple data sources, using the most appropriate techniques and tools in machine learning, pattern recognition, anomaly detection, information retrieval, or stochastic operations research
  • Articulate model results, logic, actionable recommendations to clients concisely that maximizes knowledge transfer and hastens the bottom line impact of predictive modeling
  • Leverage the predictive model information to design reports to measure emerging trends
  • Analyze and find patterns and relationships in data
  • Refine methods and processes used to extract data from large structured/unstructured datasets
  • Construct systems and algorithms to predict fraudulent behavior
  • Lead efforts to brainstorm and generate variables/indicators from both internal and external data sources
  • Work with other team members to ensure a variety of robust statistical techniques are being used to construct models


Education and Experience Requirements:

  • An undergraduate or graduate degree in Statistics, Econometrics, Mathematics, Computer Science, Management Information Systems, Engineering disciplines, or other quantitative field
  • Demonstrated ability to apply statistical techniques to solve real problems
  • Practical experience using statistical analysis techniques and building advanced/predictive models (e.g., generalized linear models, decision trees, support vector machines, neural networks, k–means clustering, co–clustering)
  • Proficiency with data mining software (e.g., SAS Enterprise Miner, SPSS PASW Modeler, Rapid–I, RapidMiner, Oracle DM)
  • Experience working with and managing large data sets with large relational databases (e.g., Teradata, Oracle, MS SQL Server) , including extraction and merges from source systems, data cleansing and transformations, and providing preliminary descriptive statistics.
  • Experience with logistics data modeling is a plus

If you meet the above requirements and are interested in the position, please send your detailed resume to no later than April 15, 2021.