Director of Data Science, Credit

Company shown to members 🔒 · Remote · US only

US only8+ years required$184K–219K/yrPublished 25 July 2025Ghost risk: high

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First recorded by Psst: 12 October 2026. Your first 3 jobs are free to apply to (the first right away, 2 more with your email). After that, the company and the apply link are for Psst members, from $4.99 for 7 days.

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The 20-second read

Experience
8+ years required
Where you can live
US only
Skills and tools
python, kubernetes
Degree or licence
Mentioned (phd)

Read from the ad by Psst's rules. Check the full ad below before applying.

Job details

Where you can work
United States
Employment type
Not stated by the employer
Advertised pay
$184K–219K/yr
Experience
8+ years required
Employer publication date
25 July 2025
First recorded by Psst
12 October 2026
Last checked at the source
10 November 2026

About the job

The company 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 the company you can get behind?

We're looking for a Director of Data Science to own the strategy and technical leadership behind the company's credit acquisition models, reporting to the Sr. Director, Data Science.

The impact you'll make

Someone hits submit on a credit card application, hopeful this is the “yes” that lets them start building toward something: a car, a home, a little more room to breathe. You'll lead the strategy and the team behind decisions like that one. Keeping every decision accurate and fair as circumstances shift makes this work interesting and rewarding, every day.

The company is young, but we’ve landed in an exciting, stable stretch of maturation: still moving toward what we’re going to become, with plenty of room for you to help shape it.

What you'll own

  • the company's credit acquisition modeling strategy, translating the company's growth and underwriting goals into a roadmap that balances approval rates, portfolio performance, and fair lending practice
  • Technical leadership for the data scientists building and maintaining acquisition models, setting the bar for model design, code quality, and production rigor
  • Model risk and monitoring practices that keep acquisition models compliant, explainable, and accurate as underwriting conditions change
  • Cross-functional alignment with Credit Risk, Portfolio, Data Engineering, and company leadership on how acquisition modeling fits into the company's broader risk appetite
  • A growing scope as acquisitions-adjacent growth initiatives roll into the team, giving you room to shape how the function expands

Our core tech stack includes

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

You'll thrive in this role if

  • You stay anchored to the business problem you're solving, keeping the modeling technique in service of the goal.
  • You're curious by nature, the kind of person who wants to understand how the pieces fit together.
  • You've made predictions where the outcome doesn't show up for a year or more, and you build in the discipline that requires, including practicing sound model risk management.
  • You can mentor and raise the technical bar for experienced data scientists without needing to be the smartest person in every room.
  • You partner naturally with people outside data science, translating technical trade-offs into decisions the business can act on.

Minimum qualifications

  • Has a PhD in a quantitative field and 5+ years of experience in a related role, or a BS/MS in a quantitative field and 8+ years of experience in a related role
  • Has created, deployed, and managed supervised learning models in a production environment for high-impact applications
  • Has direct experience hiring, coaching, and developing data scientists as their manager
  • Has applied data science to credit risk, underwriting, or another long-horizon, regulated prediction problem, such as insurance
  • Writes tested, reviewed, reproducible code, for data pipelines and model training alike, and works fluently in the Python data stack.
  • Able to travel ~4-6+ times per year for high quality in-person collaboration

Preferred qualifications

  • Direct experience in consumer lending; credit card acquisitions, specifically
  • Familiarity with the company's broader ML tooling ecosystem, including Chalk, BentoML, or DVC
  • Experience partnering directly with executive leadership on modeling strategy

Compensation

Annual full-time starting base salary range: $184,000 - $219,000

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. The company 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-first work environment.

About the company

Founded in December 2018, the company 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 the company 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 the company, earning high customer ratings on Credit Karma for its market segment and industry leading Net Promoter scores.

The company 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.

The company 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.

The company 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 [link for members] .

The company 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 the company 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.

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Ghost Job Detector: Ghost risk: high
  • Open over a year (473 days)
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