Varo is looking to leverage advanced techniques in machine learning, cloud platforms, and big data to drive decisions across the organization and propel company growth.
Requirements
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.)
Credit and / or Fraud Risk modeling experience in consumer finance is nice to have
Responsibilities
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
Other
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
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
