Engineering Manager, Machine Learning - Credit Risk

Stripe
United States
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningExperience: 3+ yearsSkills: ["Leadership","Strategic planning","Cross-functional collaboration","Engineering management"]

Lead Stripe’s Credit Risk team and shape how machine learning is used to detect and mitigate credit risk at scale. Set technical and product direction, own outcomes across credit losses, profitability, detection quality, and user experience, and guide the design and delivery of reliable ML models, services, and decision systems. Partner across engineering, product, data science, credit strategy, operations, and risk, while recruiting, hiring, and developing ML engineers.

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Stripe
Stripe
3 days ago

Engineering Manager, Machine Learning - Credit Risk

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Source: Company careers pageValidated by: Fursa AI
Last checked: 11 hours agoStatus: Live

Job Summary

Lead Stripe’s Credit Risk team and shape how machine learning is used to detect and mitigate credit risk at scale. Set technical and product direction, own outcomes across credit losses, profitability, detection quality, and user experience, and guide the design and delivery of reliable ML models, services, and decision systems. Partner across engineering, product, data science, credit strategy, operations, and risk, while recruiting, hiring, and developing ML engineers.
Location: United States
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Manager level

Key Responsibilities

  • •Set and execute strategy for detecting and mitigating credit risk through machine learning.
  • •Own outcomes related to credit losses, profitability, detection quality, and the user experience.
  • •Lead design and delivery of reliable machine learning models, services, and decision systems.
  • •Translate advances in machine learning into practical capabilities supporting business goals.
  • •Recruit, hire, and develop machine learning engineers while building an inclusive, effective team.

Key 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 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:3+ years
Skills:LeadershipStrategic planningCross-functional collaborationEngineering management
Languages:English
Tech Stack:Machine learningProduction machine learning systemsMachine learning modelsDecision systemsCredit risk detection

Company Brief

Stripe
Provides payment processing APIs and financial infrastructure for internet businesses. Powers online payments for millions of companies from startups to Fortune 500s.
Industry: Payments
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Scaleup
Valuation: Decacorn (USD 10B+)
Funding: Series E+
Headquarters: San Francisco, United States
Founded: 2010
Glassdoor
Glassdoor: 4.2
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