Data Scientist - Collection

CloudWalk; United States; Remote; USD 35,000 - 55,000; Full time

Job summary

CloudWalk is seeking a data scientist to design and implement credit card collection strategies in Brazil. You will build and refine models such as propensity to pay and risk segmentation, turn analysis into policy changes, and collaborate with engineering to deploy rules into production.

You will expand the scope with lending modeling work and explore other collection fronts as the business grows, using AI as a practical accelerator for analysis, coding, and operations, not just as a chat

Responsibilities

• Own credit card collection intelligence. Design strategies, analyses, and models built specifically for our credit card portfolio.
• Build decision models. Develop and improve models such as propensity to pay, risk segmentation, and treatment and channel optimization to drive collection actions.
• Turn data into strategy. Analyze collection performance, design experiments, and translate findings into concrete changes in policies and flows.
• Ship to production. Partner with engineering and operations to put models and rules into production and monitor their performance over time.
• Expand the scope. Collaborate with the team's lending modeling work and take on other collection fronts as the business grows.
• Use AI as a practical accelerator for analysis, coding, and operations, not only as a chat assistant.

Job description

Location: Brazil

• Own credit card collection intelligence. Design strategies, analyses, and models built specifically for our credit card portfolio.
• Build decision models. Develop and improve models such as propensity to pay, risk segmentation, and treatment and channel optimization to drive collection actions.
• Turn data into strategy. Analyze collection performance, design experiments, and translate findings into concrete changes in policies and flows.
• Ship to production. Partner with engineering and operations to put models and rules into production and monitor their performance over time.
• Expand the scope. Collaborate with the team's lending modeling work and take on other collection fronts as the business grows.
• Use AI as a practical accelerator for analysis, coding, and operations, not only as a chat assistant.
• #LI-Remote