Flex is a growth-stage FinTech company aiming to solve the problem of expensive, inflexible, and difficult rent payments by enabling users to pay rent throughout the month on a schedule that fits their finances and budget.
Requirements
- 5+ years of relevant data science experience is required.
- Proficiency in Python, SQL, or another analytical tool is a must.
- Experience in developing risk models and consumer behavior models.
- Proficiency in statistical analysis, machine learning, and data visualization tools.
- In-depth knowledge of model governance principles and practices.
Responsibilities
- Develop and implement cutting-edge risk management models, leveraging advanced statistical and machine learning techniques to effectively manage fraud/ credit financial loss on both consumers and partners sides.
- Work on the ed-to-end life cycle data science projects, from data collection and preprocessing to model development and deployment.
- Design and build model monitoring system and model governance.
- Collaborate cross-functionally with key stakeholders to understand business objectives and translate them into actionable data science strategies.
- Collaborate with engineers, compliance and product to deploy models.
- Stay up to date with the latest developments in data science and machine learning and evaluate how they can be applied to enhance our lending processes.
Other
- Experience collaborating with cross-functional teams and effectively communicating data-driven recommendations to non-technical stakeholders.
- Advanced degree in a quantitative field such as statistics, mathematics, or computer science.
- This is a hybrid position with on-site expectations of 3 days per week in our New York Headquarters.
- For candidates outside the NY/NJ area, you may be eligible for our relocation assistance program.
