Principal Data Scientist at Mission Lane

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

The impact you'll make:

Nobody wants to fall behind on a payment, but life gets in the way sometimes. How Mission Lane responds in those moments depends on the models you'll build.

What helps someone move forward isn't the same from person to person. Some respond to a text, some need a conversation, some just need more time. Working out which is which is one of the most interesting open questions here, one the field hasn't fully solved yet.

Mission Lane is young, but we've landed in an exciting, stable stretch of maturation. The collections data science practice specifically is still taking shape, so there's room to define what "good" looks like here.

What you'll own:

• Implementation of the data science roadmap for collections, serving as the primary technical point of contact day to day, and setting the standard for rigor and production quality across the data scientists, consultants, and contractors working alongside you
• End-to-end models that anticipate how customers are likely to respond to different kinds of outreach, and that shape which approach Mission Lane uses and when
• Durable internal modeling practices that reduce how much of this work needs to run through outside consultants over time

Our core tech stack includes:

Python and the PyData stack (numpy, polars, scikit-learn), LightGBM, DVC, Kubernetes, Airflow, Google Cloud, MLFlow, BentoML, and Chalk, our feature store.

You'll thrive in this role if:

• You adapt quickly to a new domain. You don't need collections experience in order to pick up the business context fast and connect it to the technical problem.
• You can trace a modeling choice back to the business problem it's solving, keeping the modeling technique in service of the goal.
• You can explain your reasoning clearly enough that consultants, contractors, and full-time teammates alike can pick up your standard and run with it.

Minimum qualifications:

• A PhD in a quantitative field and 3+ years of experience in a related role, or a BS/MS in a quantitative field and 7+ years of experience in a related role
• Has created, deployed, and managed supervised learning models in production systems for vital applications
• Shares best practices for software engineering and can help experienced data scientists work through complex technical problems, especially operationalizing and evaluating models for real-world use
• Practices solid software engineering fundamentals (test-driven development, code review, refactoring) and works fluently in our core tech stack
• Interested in a wide range of ML tooling, from established tools (Spark, Kubernetes, Airflow, MLFlow) to emerging ones (Chalk, BentoML, DVC)
• Experience assuming project leadership on a workstream, working independently with guidance focused on priorities and key objectives
• Ability to travel ~4+ times per year for high quality in-person collaboration

Compensation:

Annual full-time starting base salary range: $173,000 - $203,000

This role is eligible for additional compensation in the forms of participation in our annual incentive and equity programs.

Pay is based on factors such as work experience, education, certification(s), training, skills, and competencies related to the role. Mission Lane also offers a comprehensive benefits plan, which includes:

• paid time off
• 401(k) match
• a monthly wellness stipend
• health/dental/vision insurance options
• disability coverage
• paid parental leave
• flexible spending account (for childcare and healthcare)
• life insurance
• a remote-first work environment

About Mission Lane:

Founded in December 2018, Mission Lane is a purpose-driven fintech company based in the U.S., with headquarters in Richmond, Virginia.

It all started with a realization: nearly fifty percent of the adult population in the U.S. doesn’t have access to a clear line of credit. Most traditional credit card companies either overlook or overcharge this group because they have less-than-perfect credit scores or no scores at all. We decided this just wouldn’t do.

In partnership with our sponsor banks, we offer credit cards under the Mission Lane brand name, with better, clearer terms, and a more refined customer experience than the alternatives available to people working hard to improve their credit.To date, over four million consumers have chosen Mission Lane, earning high customer ratings on Credit Karma for its market segment and industry leading Net Promoter scores.

Mission Lane has cumulatively raised over $600 million of equity from leading investors, including Invus Opportunities, QED Investors, LL Funds, funds affiliated with Oaktree Capital Management, and other leading investors.

Our commitment to a workplace built on respect and dignity is guided by our core value of Unity. We believe that everyone plays a vital role in our shared purpose, and we actively cultivate an environment where all individuals have the opportunity to do their best work. By fostering a culture of empathy and collaboration, we create a strong sense of belonging and support for every team member.

Mission Lane is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, or any other protected status.

Mission Lane provides reasonable accommodations to applicants who need them for medical or religious reasons, as required by law. Applicants can initiate an accommodation request by contacting [e-mail].

Mission Lane is not sponsoring new applicant employment authorization and please, no third-party recruiters.

Application Integrity:

Our cardholders trust us with their financial well-being, and this trust starts with the integrity of the people on our team. We're looking for team members who share our dedication to transparency and truth.Please verify that the information in your application is accurate and complete.

Providing any information to Mission Lane that is not completely truthful at any point during the application or hiring process may result in removal from the hiring process, disqualification from future opportunities, withdrawal of an offer or other sanctions for candidates and, in addition for employees, disciplinary action, up to and including termination of employment.