Sr. Staff Data Scientist, Machine Learning
Team: Data Science
Location: San Francisco, CA, Atlanta, GA, Austin, TX, Charlotte, NC, Dallas, TX, New York City, NY, Salt Lake City, UT
Commitment: Full-time
Workplace Type: hybrid
Salary:
What you'll be doing
- 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
You'll bring the following required skills and experiences
- 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
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