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Mission Lane

Director of Data Science, Credit Risk

Reposted 21 Days Ago
Remote
Hiring Remotely in United States
185K-226K
Senior level
Remote
Hiring Remotely in United States
185K-226K
Senior level
Lead a data science team in developing machine learning models for credit risk management, driving business outcomes and team growth.
The summary above was generated by AI

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. Sound like a mission you can get behind?

About the Role

As a Director of Data Science, Credit Risk, you will lead a data science team and cross-functional projects to innovate and improve the machine learning models we rely on to make billions of dollars of efficient and accurate decisions and to enable financial progress for our customers.

As a Director of Data Science, you’ll:

Lead the design, development, and deployment of machine learning models to solve practical problems and help our business and customers reach their financial goals. You’ll partner with business leaders and technical experts across the company to develop new data sources, improve our modeling methodology, and apply models with sound risk management.

You are a person who:

  • Has experience applying data science to credit risk management and is excited to build on a multi-billion-dollar portfolio that’s growing every day
  • Can make your team better every day because you can be clear about goals and the team’s purpose. You can execute through education, organization, and trust
  • Can grow members of your team because you can help them identify their strengths and weaknesses, put them in a position to succeed, and get them the training and opportunities they need
  • Has a deep understanding of the field of data science and can communicate a vision to your team on how the field can be applied to solve difficult, practical problems
  • Has created, deployed, and managed experiments and models in production systems. You can genuinely speak to practitioners about the fundamental principles and challenges required to be successful in applied work
  • Practices solid fundamentals with software engineering (test-driven development, code review, refactoring) and the PyData stack (numpy, scikit-learn, pandas, etc.)

You get bonus points for:

  • Experience solving problems in consumer lending or fintech
  • Interest in advancing the frontiers of credit underwriting through the creation of new data sources, causal inference, and neural networks

We’re offering:

We’re committed to ensuring our team members have balance in their lives. Our comprehensive benefits package provides the support you need to thrive at work and at home.

  • Work: An engaging culture with access to training programs and advancement opportunities
  • Life: Full health, dental, and vision benefits, Flexible Spending Account (for medical and childcare expenses), paid parental leave, and a 401k Company Match
  • Balance: Generous PTO, flexible schedules, a Calm App subscription, and more

Compensation
Annual full-time base salary range: $185,000 - 226,000

Additional compensation in the form(s) of participation in our annual incentive program and equity are dependent on role.  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, and a remote-friendly 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.

Interested in learning more? Check out The Mission Lane Junction for articles on culture, credit, and community, and The Mission Lane Newsroom for media mentions.

 *****

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 [email protected].

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

Top Skills

Machine Learning
Numpy
Pandas
Scikit-Learn

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