Sr. Staff Data Scientist, Machine Learning

• Develop custom models and algorithms to apply to large datasets, as well as, processes for monitoring and analyzing their performance
• Mine and analyze data from different resources, and use predictive modeling to increase and optimize customer experiences, customer acquisition, underwriting and other business outcomes
• Assess the effectiveness and accuracy of new data sources and data gathering techniques
• Understand and apply proper risk framework to your analysis and modeling.
• Work with stakeholders throughout the organization to identify opportunities for leveraging data to drive business decisions
• Collaborate cross functionally to implement models and monitor outcomes

• 7+ years of experience in Analytics, Data Science or Data Engineering as an individual contributor
• An advanced degree in a quantitative field - computer science, engineering, statistics, operations research, economics, etc
• Credit and / or Fraud Risk modeling experience in consumer finance is nice to have
• Strong problem solving skills with an emphasis on translating real-life problems into a concrete model development strategy. Blend academic rigor with a sense of pragmatism for rapidly prototyping and delivering solutions
• Experienced in using Python for analysis and modeling
• Experience applying a wide range of statistical techniques to large data sets, and understanding their real-world advantages/drawbacks
• Experience using web services (AWS, GCP), and distributed data/computing tools (Spark, Map/Reduce, Hadoop, Hive, etc.)
• Excellent cross-functional communication skills
• Ability to thrive in a fast-paced environment

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.