Time since we first saw it
Day 28
Similar jobs usually come down between day 8 and day 57.
At Stripe, jobs usually come down by about day 60.
From 9,519 similar postings that came down, and 46 of Stripe’s. Coming down is not always a hire.
Engineering Manager, Machine Learning - Credit Risk
Location not stated
Live, first seen by us 28 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingSet and execute the strategy for detecting and mitigating credit risk with machine learning
Own outcomes for credit losses, profitability, detection quality and user experience
Lead design and delivery of reliable machine learning models, services and decision systems
Recruit, hire and develop machine learning engineers
Partner with Product, Data Science, Credit Strategy and Operations on cross-functional programs
From the employer’s posting
Set and execute the strategy for detecting and mitigating credit risk through machine learning
Own outcomes related to credit losses, profitability, detection quality, and the user experience
Lead the design and delivery of reliable machine learning models, services, and decision systems
Recruit, hire, and develop machine learning engineers while building an inclusive and effective team
Partner with Product, Data Science, Credit Strategy, Operations, and engineering teams to define priorities and deliver cross-functional programs
What you’ll bring
All qualificationsCore experience
- 3+ years of experience managing engineers who build and operate production machine learning systems
- Experience applying machine learning to complex, real-world problems and leading the technical delivery of models and supporting systems
- Experience setting strategy and working across engineering, product, data science, operations, and business teams to deliver measurable outcomes
- Experience recruiting, managing, and developing engineers in a fast-moving environment with significant autonomy
Preferred experience
- Experience with credit risk, fraud detection, financial risk, trust and safety, or another domain involving decisions under uncertainty
- Experience balancing risk reduction with customer or user experience
- Experience building machine learning systems that support high-stakes, time-sensitive decisions at scale
- Experience setting a multi-year technical direction while delivering progress through quarterly plans
Qualification wording
3+ years of experience managing engineers who build and operate production machine learning systems
Experience applying machine learning to complex, real-world problems and leading the technical delivery of models and supporting systems
Experience setting strategy and working across engineering, product, data science, operations, and business teams to deliver measurable outcomes
Experience recruiting, managing, and developing engineers in a fast-moving environment with significant autonomy
Experience with credit risk, fraud detection, financial risk, trust and safety, or another domain involving decisions under uncertainty
Experience balancing risk reduction with customer or user experience
Experience building machine learning systems that support high-stakes, time-sensitive decisions at scale
Experience setting a multi-year technical direction while delivering progress through quarterly plans
About Stripe
Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead.
In the employer’s words · Read in context
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 17, 202628 days ago
- Recorded sightings
- 133
- Last seen by us
- Nov 14, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Stripe is hiring
35 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring is picking up
- Takes jobs down at a usual pace
See how this role fits your experience
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Your next step
Complete your application on stripe.com. The employer’s form will show what is required.
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- No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
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Demand for Data Leadership roles
New Data Leadership postings at the employers we follow are about the same over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Leadership, by the work the posting describes.
Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.
Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.
Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.
US government figures for computer and information systems managers
- Median yearly pay, May 2025
- $175,140
- Expected change, 2025 to 2035
- 15.8% more jobsagainst 3.5% for all jobs
The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.
Job description
Engineering Manager, Machine Learning Credit Risk
Who we are
About Stripe
Stripe is a financial infrastructure platform for businesses. Millions of companies from the world’s largest enterprises to the most ambitious startups use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.
About the team
The Credit Risk team develops intelligent systems that help Stripe identify high-risk accounts, minimize credit losses, and improve profitability. Credit risk is a complex machine learning problem that requires us to distinguish emerging risk from healthy business activity while giving legitimate users a clear and reliable experience.
Our team consists of machine learning engineers who build models and systems used across Stripe’s credit-risk products. We work closely with partners in Product, Data Science, Credit Strategy, Operations, and other engineering teams. Together, we help stakeholders make informed decisions and support sustainable growth wherever credit risk affects Stripe’s products.
What you’ll do
We’re looking for an engineering manager to lead the Credit Risk team and shape how Stripe uses machine learning to manage credit risk at scale. You’ll set the team’s technical and product direction, connect advances in machine learning to measurable business outcomes, and help engineers deliver reliable systems that balance loss prevention with the user experience.
You’ll work across engineering, product, data science, and risk to identify the highest-impact opportunities and turn them into a focused roadmap. You’ll also hire and develop engineers, strengthen the team’s technical practices, and contribute to machine learning and engineering leadership across Stripe.
Responsibilities
- Set and execute the strategy for detecting and mitigating credit risk through machine learning
- Own outcomes related to credit losses, profitability, detection quality, and the user experience
- Lead the design and delivery of reliable machine learning models, services, and decision systems
- Translate advances in machine learning into practical capabilities that support the team’s business goals
- Partner with Product, Data Science, Credit Strategy, Operations, and engineering teams to define priorities and deliver cross-functional programs
- Recruit, hire, and develop machine learning engineers while building an inclusive and effective team
- Contribute to broader engineering and machine learning initiatives as a member of Stripe’s engineering management team
Who you are
We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.
Minimum requirements
- 3+ years of experience managing engineers who build and operate production machine learning systems
- Experience applying machine learning to complex, real-world problems and leading the technical delivery of models and supporting systems
- Experience setting strategy and working across engineering, product, data science, operations, and business teams to deliver measurable outcomes
- Experience recruiting, managing, and developing engineers in a fast-moving environment with significant autonomy
Preferred qualifications
- Experience with credit risk, fraud detection, financial risk, trust and safety, or another domain involving decisions under uncertainty
- Experience balancing risk reduction with customer or user experience
- Experience building machine learning systems that support high-stakes, time-sensitive decisions at scale
- Experience setting a multi-year technical direction while delivering progress through quarterly plans
- Experience managing geographically distributed teams
Source details
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