Job Description
Flex is an early-stage, remote-first FinTech startup that is creating the best rent payment experience. It’s hard to believe that it’s 2023 and paying rent on time is expensive, inflexible, and difficult. We’re here to change that! We enable our users to pay rent throughout the month on a schedule that better fits their finances and budget. Our mission is to empower as many renters as possible with flexibility over their most significant recurring expense. After deliberately keeping a stealth profile as we built up unprecedented investor support and an enthusiastic user base, we are looking for motivated individuals to help us keep our mission growing in 2023. Will you be a part of the team?Â
The goal of the risk data science team is to leverage our extensive data assets to identify insights and trends, develop predictive models, and generate actionable recommendations that enable Flex to deliver the best possible products and services to our customers. As a leader on the team, you’ll partner closely with teams & leadership across the organization to create data science roadmaps, identify opportunities for growth, and drive a deeper understanding of our business.
What you’ll do:
- Collaborate with business stakeholders from Policy, Product, Data and Engineering to identify, test, and implement data science solutions that drive business and customer success
- Develop and own a roadmap in collaboration with stakeholders to organize and prioritize initiatives
- Own full-cycle of risk models from ideation and training through deployment into our production environment
- Work with product and engineering to build out and improve the infrastructure for modeling and machine learning
- Become an expert on data sources and a thought leader in applying data science to understand and improve our business and operations
- Grow the data science function to meet the growth needs of the businessÂ
What you’ll bring:
- Bachelor's degree is in Statistics or an equivalent quantitative field
- 5+ years experience of statistical modeling experience in R, SQL, Python, or SAS
- 3+ years experience building credit risk models for underwriting and/or portfolio management
- Experience working with raw bureau data
- Expertise in predictive modeling (including linear and logistic regression, decision trees, random forest, and gradient boosting)
Bonus points if you have:
- MS degree is in Statistics or an equivalent quantitative field
- Hands-on experience with cloud infrastructure such as AWS or GCP
- Passionate about solving problems with data and a high level of intellectual curiosity
- Highly motivated to work on multiple projects and a team player with a startup spirit
- Very strong written and oral communication skills
- Competitive pay
- 100% company-paid medical, dental, and vision
- 401(k) + company stock options
- Unlimited paid time off + company paid holidays
- Parental leave + IVF and adoption support
- Flex Cares Program: Non-profit company match + pet adoption coverage
- Free Flex subscription
Date Posted
03/17/2023
Views
6
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