Senior Product Manager, Credit Line Platform

About the role

Customers in emerging markets access pathways to financial stability and success through these offerings.

Data roles turn raw information into decisions. Analysts query databases and build dashboards. Data scientists build models that predict outcomes. Data engineers build the pipelines that move and store data. All three work closely with business teams and need a mix of statistics, coding, and communication. Nearly every modern company runs on data teams, from startups to banks. A strong portfolio of past analyses matters more than degrees in many hiring decisions.

Key facts

What you'll do

The role scopes the roadmap to align with business goals, coordinating engineering and operations for prioritized delivery across loan and line products, including point-of-sale financing.

Cross-functional collaboration with engineering and operational teams delivers impactful products that meet customer needs and regulatory expectations for loan servicing.

Data-driven analysis and SQL execution validate performance, surface insights, and guide iterative improvements to credit line workflows and payments.

Platform services design specifies algorithms, data structures, and platform services to support scalable credit line management and card offerings.

Operational execution balances customer-first solutions with security controls and efficiency in servicing loan and line products, including amortization and customer invoicing.

Requirements

Five or more years of product management experience in fintech, preferably focused on Loan Management Systems or loan servicing within credit line products.

Proven experience driving cross-functional teams to deliver impactful products in fast-paced settings with point-of-sale financing.

Capacity to manage and prioritize multiple initiatives simultaneously while maintaining execution speed for emerging markets.

Strong proficiency in data-driven decision-making, including the ability to write and interpret SQL queries for underwriting and payments.

Ability to define algorithms, data structures, and platform services that support lending operations and anti-fraud AI.

Familiarity with Loan Management Systems, underwriting, and servicing operations in both loan and line products including amortization and customer invoicing.

A track record of designing customer-first solutions while balancing security and operational efficiency for public benefit operations.

A bachelor's degree or equivalent practical experience as stated in the degree requirement for the role.

Practical notes

Payjoy is a Public Benefit Corporation and an Equal Employment Opportunity employer.

Work location and team details are confirmed Typical interview steps

Data interviews commonly include a SQL or coding exercise, a statistics question, and a case study. Candidates may be asked to design a metric, interpret an experiment, or build a small model. Some companies give a take-home analysis. Expect questions about past projects and the business impact of your work. Interviewers often evaluate how you communicate uncertainty and business impact, not only the math. Bringing a clean write-up of a past analysis to the interview is well received.

Good to know

This role focuses on credit line platforms in fintech, using modern data and machine learning methods.

The team applies anti-fraud AI, data science, and automated decisioning to manage risk at scale for financial inclusion.

These products serve a large customer base and support financial inclusion in emerging markets.

Questions to ask

Good questions to ask the employer in the interview: what does success look like in the first six months, how is the team structured, what is the current biggest challenge, and how are decisions made. Asking about growth paths and the review process is also well received. Employers expect questions, and good ones show preparation.

Career growth

Data careers grow toward senior analyst, staff data scientist, or data engineering lead. Many professionals specialize in machine learning, analytics, or infrastructure. Cross-functional work with product and engineering teams becomes more important at senior levels. The field changes quickly, so continuous learning is part of the job. Professionals who can translate numbers into decisions tend to advance fastest.