• Develop predictive risk management and business intelligence solutions for credit card issuers, auto and mortgage lenders, personal finance lenders, and telecommunications. Partner with internal and external crossfunctional teams to drive new business initiatives and deliver long term value-added product proposition for customers in the U.S. financial services segment.
• Design and lead client facing engagements involving descriptive, predictive, and prescriptive analysis leveraging a variety of techniques such as segmentation, logistic regression, gradient boosted machines, survival analysis, principal component analysis, sensitivity analysis, and novel machine learning techniques. Technical environment: Data Analytics,
• SQL, R, Python,
• Hadoop, Tableau,
• Machine Learning Algorithms,
• Data Mining Techniques, Business Statistics.

• Master’s degree in Statistics,
• Applied Mathematics,
• Financial Mathematics,
• Computer Science, management information systems, or a related field plus two years of experience in the job offered, as a data analyst, or performing data analytics required.

Required skills:

• 2-years of experience in a client facing role involving descriptive, predictive, and prescriptive data analysis; experience with
• Data Analytics,
• SQL, R, Python, Hadoop,
• Tableau, Machine Learning Algorithms,
• Data Mining Techniques, Business Statistics.
• Telecommuting permitted.