Translating unstructured business problems into well-defined machine learning projects. Collaborating with a cross-functional team of Engineers, Product Managers, and Business Analysts to identify and manage high leverage opportunities for modeling work. Designing and implementing highly generalizable models for predicting various outcomes. Taking responsibility for modeling implementation in real world settings to solve real world problems. Mentoring junior team members in modeling artistry. Visibly driving innovation by incorporating new modeling capabilities and/or pioneering data sources. Developing and evangelizing best practices for scoping, building, validating, and monitoring modeling projects. As needed travel with Data Science Team to meet clients, approximately 10%.

Master's degree in industrial engineering, statistics, math, physics or related field plus 3 years of experience. 3 years of experience with designing and developing machine learning models/algorithms. 2 years of experience with programming in r or python. 1 year of experience with designing and implementing highly generalizable models for predicting various outcomes. 1 year of experience with data structures and parallelization. 1 year of experience taking responsibility for modeling implementation in real world settings to solve real world problems.

Must also have authority to work permanently in the U.S. Applicants who are interested in this position may apply at www.jobpostingtoday.com (ref # 19590) for consideration.

About ZestFinance:

ZestFinance, Inc. applies its unique credit-decisioning technology platform — based on data science and machine learning — to help lenders effectively predict credit risk so they can increase revenues, reduce risk and ensure compliance. ZestFinance was founded in 2009 by Douglas Merrill and a team of former Google employees with the mission of making fair and transparent credit available to everyone.

We are committed to diversity in hiring, professional development, and everyday discussion. Zest is determined to hire crazy smart people who are different from each other to create broad thinking, lots of different ideas, and by extension, the best team possible.