Principal Data Scientist

Mission Lane

2d•$173,000 - $203,000•Remote

About The Position

Mission Lane is combining the power of data, technology, and exceptional service to pave a clear way forward for millions of people on the path to financial success. By attracting top talent and leveraging cutting-edge technology, we’re enabling people to unlock real financial progress. We're looking for a Principal Data Scientist to be the technical anchor for Mission Lane's collections models, reporting to the Director, Data Science. 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.

Requirements

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

Nice To Haves

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.

Responsibilities

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