As a Data Scientist, you will use your math wizardry to develop radically new methods for data access, manipulation, and modeling that will enable us to provide fair, transparent credit alternatives to underbanked Americans.
Successful candidates will be crazy smart, creative thinkers who are capable of devising innovative solutions to old financial problems. They will interface directly between our engineering and modeling teams to validate our current models and develop tools to make the core modeling team more efficient. As our name implies, we work with a great deal of enthusiasm and energy along with a social conscience and passion for leveraging data and technology to transform financial services as we know it.
Skills & Requirements
- Design and implement statistical tools for developing and validating new models
- Validate models for roll-out and analyze the performance of existing models
- Assess the usefulness of new data sources, transformations, and techniques
- Support other team members with their modeling and analysis projects
- Work with the Product Management, Marketing, and Business teams to develop models to support specific business needs
- 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 Math, Computer Science, Statistics, Biostatistics, or related discipline; Advanced degrees preferred
- Extensive use of R Matlab, or Python, and Linux
- Understanding of statistical analysis, algorithm development, and advanced machine learning techniques
- Commitment to creating reproducible, well-documented code
- An independent and self-motivated work ethic
- A proven, demonstrable track record of success
ZestFinance was founded in 2009 by Douglas Merrill, former CIO of Google, along with a team of data scientists from Google and lending experts from Capital One. Together they set about revolutionizing credit underwriting for underbanked Americans.
As it stands today, good people are being denied credit because old world processes do not take advantage of today’s data rich environment. ZestFinance applies machine learning and large-scale data analysis to evaluate thousands of potential credit variables.
Using this more sophisticated approach, ZestFinance can better assess default risk and the viability of a long-term customer relationship allowing the company to offer loans at a fraction of the rates of its competitors. The company also makes its technology platform available to other organizations, enabling them to use data to make smarter underwriting and business decisions.