远程工作雷达

数据科学总监,信用

Director of Data Science, Credit

其他限定地区(需当地身份)
公司missionlane
薪资未公开
工作地点Remote, United States
地域资格限定地区(需当地身份)
时区要求无特别要求
用工类型未标注
发布时间2025-07-25
数据来源Greenhouse
前往企业招聘页投递 →
注意地域限制:该职位明确限定在 Remote, United States 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。

Mission Lane 正在利用数据、技术和卓越服务的力量,为数以百万计的人铺平通往财务成功的道路。通过吸引顶尖人才并运用前沿技术,我们帮助人们实现真正的财务进步。听起来这正是你想要投身的使命吗?

我们正在寻找一位数据科学总监,负责 Mission Lane 信用获取模型的战略和技术领导工作,向高级数据科学总监汇报。

你将带来的影响:

当有人提交信用卡申请时,他们希望这是那个“批准”的答复,让他们开始迈向某件事情:一辆车、一套房子,或者更多的喘息空间。你将领导背后做出此类决策的战略和团队。随着情况的变化,确保每个决策准确且公平,让这项工作每天都有意义且有回报。

Mission Lane 还很年轻,但我们正处于一个令人兴奋且稳定的成熟阶段:仍在朝着我们未来的样子前进,而你有很多机会参与塑造它。

你将负责:

  • Mission Lane 的信用获取建模策略,将公司的增长和承销目标转化为平衡审批率、投资组合表现和公平借贷实践的路线图
  • 领导构建和维护获取模型的数据科学家团队,设定模型设计、代码质量和生产严谨性的标准
  • 模型风险和监控实践,确保获取模型在承销条件变化时保持合规、可解释和准确
  • 与信用风险、投资组合、数据工程和公司管理层进行跨职能协作,明确获取建模在 Mission Lane 更广泛的风险偏好中的位置
  • 随着与获取相关的增长计划逐步纳入团队,你将有机会塑造该职能的扩展方式

我们的核心技术栈包括:

Python 和 Python 数据栈(numpy、polars、scikit-learn)、LightGBM、DVC、Kubernetes、Airflow、Google Cloud,以及我们的特征存储 Chalk

如果你具备以下特质,你会在这个职位上表现出色:

  • 你始终围绕所解决的业务问题展开,让建模技术服务于目标
  • 你天生充满好奇心,是那种希望理解各个部分如何协同工作的类型
  • 你曾做过预测,其结果需要一年或更长时间才能显现,你具备为此所需的自律,包括建立良好的模型风险管理实践
查看英文原文

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?

We're looking for a Director of Data Science to own the strategy and technical leadership behind Mission Lane'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.

Mission Lane 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:

  • Mission Lane'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 Mission Lane'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 Mission Lane'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. 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-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 peopleexperience@missionlane.com.

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.

本页面信息整理自 Greenhouse,版权归原发布方所有。职位可能随时关闭,投递请以原始页面为准。 本站只做信息聚合展示,不参与招聘流程,也不向求职者收取任何费用。

该公司其他在招职位

执行助理

missionlaneRemote, United States6 天前
其他限定地区(需当地身份)

← 返回全部职位