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Assistant Vice President
CIT
Pasadena, CA, United States
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Overview
Founded in 1908, CIT (NYSE: CIT) is a financial holding company with approximately $50 billion in assets as of Dec. 31, 2017. Its principal bank subsidiary, CIT Bank, N.A., (Member FDIC, Equal Housing Lender) has approximately $30 billion of deposits and more than $40 billion of assets. CIT provides financing, leasing, and advisory services principally to middle-market companies and small businesses across a wide variety of industries. It also offers products and services to consumers through its Internet bank franchise and a network of retail branches in Southern California, operating as OneWest Bank, a division of CIT Bank, N.A. For more information, visit cit.com.
Responsibilities
• Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
• Develop and execute upon data A/B testing framework and test model quality.
• Coordinate with different functional teams to implement models and monitor outcomes.
• Create and use advanced machine learning algorithms and statistics: regression, distributions, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc
• Work to analyze data from a wide variety of 3rd party data providers: Google Analytics, Adwords, Facebook Insights, etc.
• Use distributed data/computing tools to achieve business results: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
• Work with cloud and distributed computing architectures, and data providers, e.g S3, Spark, DigitalOcean, Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL
Qualifications
• 5+ years’ experience in analytics and data science
• Master’s Degree in Computer Science, Statistics, Applied Math or related field
• 7+ years’ practical experience with SAS, ETL, data processing, database programming and data analytics
• Extensive background in data mining and statistical analysis
• Able to understand various data structures and common methods in data transformation
• Excellent pattern recognition and predictive modeling skills
• Experience with programming languages such as Java/Python an asset
• Preferable experience working with Financial Firms or Ad Agencies