Consultants, Data Science and Analytics for White Plains, NY location. Analyze results of statistical and empirical data models to assist in the development of business solutions for the company's financial services clients. Participate in the design and execution of data mining tools to extract data, analyze data and build functional data models. Create test transactions and oversee run tests by analysts to identify logic errors in statistical analysis programs and modify programs to eliminate errors. Solve data errors through business knowledge of the credit industry and use of run tests. Develop predictive and survival models and mine longitudinal time-series industry database to build payment and customer behavior forecasting models. Identify relationships and trends in data collection, as well as any discernable trends, variables or factors that could affect the results of statistical analysis to verify the analysis and research. Evaluate all sources of data and information in order to determine any limitations in terms of reliability or usability for modeling and statistical analysis projects. Technical environment: statistical and coding tools (SAS, R, Python); machine learning model development (gradient boosting machines, support vector machines, decision trees, regression techniques); structured databases; analysis and manipulation of complex and high volume credit data from varying sources; T-SQL; AWS redshift; Tableau. Master’s degree in Computer Science, Data Analytics, Information Systems, Statistics, or related Quantitative field plus two years of experience with Credit/Financial industry data required. Required skills: statistical and coding tools (SAS, R, Python); machine learning model development (gradient boosting machines, support vector machines, decision trees, regression techniques); structured databases; analysis and manipulation of complex and high-volume credit data from varying sources; T-SQL; AWS redshift; Tableau. Some telecommuting permitted. 37.5hrs/wk

Minimum Salary: 80000 Maximum Salary: 107127 Salary Unit: Yearly