About the Role
We are partnering with a well-funded consumer lending fintech to find a Lead Data Scientist to serve as the technical lead for its machine learning function focused on customer operations and collections strategy.
This is a senior individual contributor role, not a people management position. You will set modeling standards, drive the day-to-day technical roadmap, and serve as the primary technical resource for internal Data Scientists, external consultants, and specialist contractors.
The team is working to better understand how customers respond to different collection strategies and communication channels. By using customer interaction data and predictive modeling, you will help develop production-ready decisioning systems that improve customer engagement and repayment outcomes.
With significant funding, established operations, and large volumes of customer interaction data, the organization offers an opportunity to shape the future direction of its collections data science capabilities.
Key Responsibilities
•Drive execution of the collections data science roadmap and prioritize modeling initiatives.
•Serve as the lead technical authority across machine learning and predictive modeling projects.
•Build machine learning models to predict customer responses, engagement patterns, and repayment behavior.
•Develop data-driven strategies to inform how and when customers are contacted across different communication channels.
•Establish scalable modeling, testing, and experimentation frameworks.
•Improve engineering practices and production standards across the wider data science team.
•Provide technical guidance to internal Data Scientists, external consultants, and specialist contractors.
•Reduce reliance on external consultancies by developing sustainable internal technical capabilities.
•Promote reliable, reproducible, and maintainable machine learning workflows.
Technology Stack The team works with a modern machine learning and cloud infrastructure stack, including:
•Python
•Scikit-learn and LightGBM
•Airflow
•Kubernetes
•Google Cloud Platform (GCP)
•MLflow
•BentoML
•Chalk Feature Store
•DVC
Required Qualifications
•At least 7 years of commercial Data Science experience or an equivalent advanced academic background.
•Demonstrated experience deploying and monitoring machine learning models in production.
•Strong software engineering practices, including testing, code reviews, and reproducibility.
•Experience leading technically complex projects and influencing senior stakeholders.
•Ability to operate independently as the most senior individual contributor within a workstream.
•Experience in fintech, consumer lending, risk, operations, marketing science, or another environment involving large-scale predictive modeling.
Preferred Qualifications
•Previous experience in collections data science.
•Strong interest in MLOps and production machine learning.
Compensation and Benefits
•Base Salary: Up to $200,000 per year.
•Additional Compensation: Bonus and equity.
•Benefits: Full benefits package.
•Work Arrangement: Fully remote within the United States.
About the Opportunity
This role offers the opportunity to influence the technical direction of a growing machine learning function within consumer lending. You will work with substantial customer interaction data, build models that inform real-world collections decisions, and establish the technical foundations for long-term data science capabilities.