Senior Associate Machine Learning Modeler / Data Scientist

ZestFinance is a technology startup that uses machine learning and large-scale data analysis to transform credit availability for millions of Americans. Over the past 5 years, ZestFinance has built a big data underwriting technology that more accurately predicts likelihood of repayment. ZestFinance uses this technology to make loans to customer that banks typically overlook. ZestFinance also licenses its technology to other companies, including JD.com in China.

As a Machine Learning Modeler at ZestFinance, you will use your modeling artistry to develop radically new methods for manipulation and prediction that will enable us to provide fair, transparent credit alternatives to underbanked Americans. Using a combination of machine learning technology and vast amounts of data sources, we seek to transform the credit market while expanding our team into interesting and revolutionary frontiers within the credit world.

* Design and implement highly generalizable models for predicting various outcomes. * Taking responsibility for modeling implementation in real world settings to solve real world problems. * Work with Product Management, Marketing, and Business Analysis to develop models to support specific business needs. * Mentor junior team members in modeling artistry. * Feel good about coming to work and enjoy not only the time you spend at the office, but the people you’re spending it with as well.

* Bachelor’s Degree in a quantitative discipline; advanced degrees preferred. * Expert experience designing, developing, and implementing machine learning models / algorithms. * A proven, demonstrable track record of success. * Extensive programming experience in one or more of the following: R, Python, Julia, Vowpal Wabbit and an interest in learning new languages and technologies. * Knowledge of data structures and parallelization. * Successful Kaggle competition experience is strongly desired. * Experience with large scale data storage and analysis (e.g., Spark, MapReduce) is a plus.