Varo Bank
San Francisco
501-1,000 employees
Varo is an entirely new kind of bank. All digital, mission driven, FDIC insured and designed for the way our customers live their lives.
Other Open Roles
Prior Listings
- Sr. Data Analyst
- Lead Fraud Data Analyst
- Sr. Software Engineer, Machine Learning
- Lead Machine Learning Scientist, Lending
- Staff Data Engineer
- Senior Data Scientist, Machine Learning
- Sr. Data Engineer
- Lead Machine Learning Scientist, Fraud
- Sr. Data Engineer
- Principal Engineer, Data Engineering
- Director of Data Science
- Sr. Risk Data Analyst
- Lead Data Scientist, Acquisition
- Sr. Machine Learning Engineer
- Sr. Analyst, Data Science - Model Risk Management
- Sr. Data Analyst, Commercial Analytics
- Sr. Software Engineer, Data (Backend)
- Sr. Data Analyst, Payments
- Sr. Product Manager, Data
- Staff Data Scientist, Machine Learning (Fraud)
Sr. Staff Data Scientist, Machine Learning
Sr. Staff Data Scientist, Machine Learning
This job is no longer open
Each member of the Data team plays an integral part of what we are building at Varo. We rely on advanced techniques in machine learning, cloud platforms and big data to drive decisions across the organization. If you are interested in working with an impressive team of Data pros who collaborate and challenge each other, and want to solve interesting problems to propel the company’s growth, apply now!
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
$210,000 - $250,000 a year
For cash compensation, we set standard ranges for all US-based roles based on function, level, and geographic location, benchmarked against similar-stage growth companies. Per applicable law, the salary range for this role is $210,000 - $250,000. Final offer amounts are determined by multiple factors as well as candidate experience and expertise and may vary from the identified range.
#MidSenior
This job is no longer open