Principal Data Scientist, Collections ML Strategy

Matcha; Northern (KY); Hybrid; USD 173,000 - 203,000; Full time

Benefits offered by this job

Remote-first environment

401(k) match

Wellness stipend

Health/dental/vision insurance

Job summary

Mission Lane is seeking a senior data scientist to own the collections data science roadmap and serve as the primary technical contact for the team. You will shape end-to-end models predicting customer responses to outreach and lead durable modeling practices for long-term efficiency.

The role leverages Python, the PyData stack, and tools like LightGBM, DVC, Kubernetes, Airflow, and MLFlow to deliver production-grade solutions.

Qualifications

• PhD in a quantitative field with 3+ years in a related role or BS/MS with 7+ years in a related role.
• Experience creating, deploying, and managing supervised learning models in production systems.
• Ability to share best practices for software engineering and help data scientists with complex problems, especially operationalizing/evaluating models.
• Solid software engineering fundamentals (TDD, code review, refactoring) in our core tech stack.
• Interest in ML tools from Spark/Kubernetes/Airflow/MLFlow to Chalk/BentoML/DVC.
• Experience leading a workstream independently with guidance on priorities.
• Willingness to travel ~4+ times per year for in-person collaboration.

Responsibilities

• Implement the data science roadmap for collections and set standards for quality across teams.
• Develop end-to-end models predicting customer responses to outreach and guide business decisions.
• Establish durable modeling practices to reduce reliance on external consultants over time.

Skills

Modeling

Communication

Leadership

Experimentation

Education

PhD in quantitative field

BS/MS in quantitative field

Tools

Spark

Kubernetes

Airflow

MLFlow

DVC

Chalk

BentoML

LightGBM

Job description

Mission Lane is seeking a senior data scientist to own the collections data science roadmap and serve as the primary technical contact for the team. You will shape end-to-end models predicting customer responses to outreach and lead durable modeling practices for long-term efficiency.

The role leverages Python, the PyData stack, and tools like LightGBM, DVC, Kubernetes, Airflow, and MLFlow to deliver production-grade solutions.