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　　Job Description

　　Consultants for various and unanticipated worksites throughout the U.S. (HQ: Chicago, IL). Partner with internal and external cross-functional teams to drive new business initiatives and deliver long term value-added product propositions for customers. Develop predictive risk management and business intelligence solutions for credit card issuers, auto & mortgage lenders, collections agencies, and retail banks. Participate in projects on analytic engagements involving descriptive, predictive, and prescriptive analysis through the consumer lending portfolio lifecycle, leveraging a variety of techniques (e.g., segmentation, logistic regression, survival analysis, principal component analysis, machine learning models, scenario and sensitivity analysis). Design and write programs for data extraction, segmentation, and statistical analysis on datasets at scale. Deliver analytic insights and recommendations in succinct and compelling presentations for internal and external customers and an executive audience. Technical Environment: R, Python, SQL, PySpark, Shell Scripting, R Studio, MySQL, Hadoop, Spark-SQL, Hive, Pig, Sparklyr, PyCharm, Tableau, Gephi, SQL Assistant, GCP, AWS, RESTful web services, machine learning, segmentation, logistic regression, survival analysis, principal component analysis, scenario and sensitivity analysis.

　　Job Requirements

　　Master's degree in Statistics, Analytics, or a related field plus two years of experience in the job offered, in financial services, as an Analyst, or with data analytics required. Required skills: R, Python, SQL, PySpark, Shell Scripting, R Studio, MySQL, Hadoop, Spark-SQL, Hive, Pig, Sparklyr, PyCharm, Tableau, Gephi, SQL Assistant, GCP, AWS, RESTful web services, machine learning, segmentation, logistic regression, survival analysis, principal component analysis, scenario and sensitivity analysis. Telecommuting permitted. ( Bachelor's degree in Statistics, Analytics, or a related field plus five years of progressive experience in the job offered, in financial services, as an Analyst, or with data analytics also acceptable).