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Data Scientist - Credit Risk

Company: Pipetechnologies

Location: Remote

Posted on: November 24

About Pipe

Pipe is a new kind of trading platform that enables entrepreneurs to grow their businesses on their terms. By treating recurring revenue streams as an asset, Pipe allows companies to transform their recurring revenue into up-front capital, instantly. For entrepreneurs, that means more cash flow for scaling a business without dilution or restrictive debt. For investors, Pipe has unlocked a previously untapped asset class. Whether youre an entrepreneur or an investor, Pipe is growth on your terms.

Were a fully distributed, remote-first, fast-growing startup. Our engineering, data science and risk teams are spread from UTC-8 to UTC+6 and we rely heavily on our written communication skills in order to make it work. We believe in giving our team agency and control over their schedules: we avoid standing meetings, and default to asynchronous communication. There are no core working hours, we just ask our team to communicate clearly about their schedules and be considerate to their coworkers if plans change. You will occasionally need to be flexible in order to meet synchronously with colleagues in different time zones.

The Role

This is a full-time, fully-remote position as a Credit Risk Data Scientist. In this role, you will:

  • Use analytics and statistical modeling to understand and operationalize drivers of credit risk.
  • Own the end-to-end development lifecycle of credit risk models, from prototyping and testing to deployment in production.
  • Be the link between the data science & risk functions, working closely with both to improve risk modeling for Pipe's revolutionary asset class.
  • Work with our Sales and Marketing teams to originate deals with the right risk profile.


We are looking for talented data scientists with past experience in a similar role. Specifically, ideal candidates will have:

  • Experience in credit risk and/or quantitative finance. Prior work in SMB underwriting is a plus.
  • Proficiency in SQL and at least one scripting language.
  • Sound fundamentals in probability and statistics.
  • Familiarity with analyzing financial statements.
  • Bachelor's degree in Financial/Applied Math, Operations Research, Economics, and/or Statistics. Masters/PhD is a plus.
  • Strong written and verbal communication skills.

In general, you will be successful at Pipe if:

  • You want to join a quickly growing startup and make an impact.
  • You want to be part of a team that holds each other to high standards.
  • You have a strong technical foundation, and are passionate about using your toolkit to help our customers succeed.
  • You take end-to-end ownership of your work and enjoy working with different functions across the company.
  • You have strong written and verbal communication skills.
  • You want to work in an environment that values and rewards excellence.

Many good candidates do not fit job descriptions perfectly. If you believe you are a good fit, we encourage you to apply. Pipe is an equal opportunity employer: we do not discriminate. Inclusion is important to us and we hope it is to you, too.

Tech Stack

We are committed to using the right tools for the problems we are trying to solve. Currently our stack is mostly comprised of:

  • PostgreSQL, Bigquery, Spark, Superset, Baseten, Dataform
  • We are primarily a Python and Go shop, but experience in other languages will translate. As an early member of the data science team at the company, you will have the opportunity to define our stack for the future as well.

Compensation and Benefits

  • We want you to feel like an owner and that will be reflected in your salary and equity.
  • The best equipment: if you want it, and it helps you do your job, we'll provide it. Computers, monitors, desks, chairs, headphones, speakers, microphones, webcams, keyboards, mice, etc.
  • A good work-life balance: we do our best work when we regularly can step away from it and live our lives.
  • Flexible vacation and work hours. We don't adopt conventional work practices that are meaningless for the type of work we do.
  • Parental leave for anyone who is growing their family, regardless of gender.
  • Very good health, dental, and vision insurance.
  • Great colleagues: we value a culture of authenticity, humility, and excellence.