About the role

As a data scientist on the Risk and Data Science team, you will be responsible for data science projects in the risk domain. You will be directly developing machine learning models with the goal of maximizing LTV.

What you’ll do

• 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 end-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.
• Experience on credit line assignment and risk based pricing modeling is a plus.

Key qualifications

• Advanced degree in a quantitative field such as statistics, mathematics, or computer science.
• Proficiency in R/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.
• Experience collaborating with cross-functional teams and effectively communicating data-driven recommendations to non-technical stakeholders.
• In-depth knowledge of data governance principles and practices.
• Minimum 2~3 years of relevant data science experience is required.

The national pay range for this role is $125,000-$145,000 in base salary. Individual compensation will be commensurate with the candidate's experience aligned with Flex's internal leveling guidelines and benchmarks.