Lead Data Scientist
The Lead, Data Scientist will lead Zest’s ML team to deliver technically excellent, highly predictive yet explainable models to drive Zest’s businesses. The Lead, Data Scientist will also communicate and champion Zest’s underwriting technologies to external constituencies including conferences, press, and potential clients.
You will lead the team to develop radically new methods for manipulation and prediction that will enable us to provide fair, transparent credit. 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.
In this role you will:
- Lead a team of 5+ data scientists in developing high-quality, robust, predictive and explainable algorithms that produce robust and scalable real-time predictions
- Define Zest’s modeling strategy and manage pipeline for internal and external modeling efforts
- Translate unstructured business problems into well-defined machine learning projects
- Collaborate with a cross-functional team of Engineers, Product Managers, and Business Analysts to identify and manage high leverage opportunities for modeling work
- Represent ZestFinance in calls, meetings, conferences to advance Zest’s position as the world’s leading ML team
- Visibly drive innovation by incorporating new modeling capabilities and/or pioneering data sources
- Develop and evangelize best practices for scoping, building, validating, and monitoring modeling projects
- Recruit, motivate and develop members of the data science team
We are looking for:
- Masters/PhD Degree in Math, Computer Science, Statistics, or a related quantitative field.
- Expert command of statistical analysis, algorithm development, and state-of-the-art tools and methodologies for data science
- 5+ years creating predictive models using advance machine learning techniques
- 2+ years managing a team of data scientists
- Expert command of SQL and R or Python as applied to data science
- Experience developing real-time production data pipelines
- Experience interacting with external clients is a plus