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3 месяца назад

Machine Learning Lead (Fintech)

225 000 - 275 000$
Формат работы
onsite
Тип работы
fulltime
Грейд
lead
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Machine Learning Lead (Fintech): Building and deploying fraud detection and risk decisioning models for high-volume payment flows with an accent on transaction data, feature engineering, and acquiring-side payments fraud. Focus on owning the full model lifecycle, integrating external fraud partners, and establishing scalable MLOps and ML practices.

Location: Chicago, United States; on-site

Salary: $225,000–$275,000 USD base salary per year, plus performance bonus and equity.

Company

hirify.global is a fintech payment service provider using stablecoins, AI-driven fraud prevention, instant settlement, global pay-ins, multi-currency FX, and unified payouts for marketplaces, fintechs, remittance providers, gaming platforms, and ecommerce merchants.

What you will do

  • Lead the first dedicated ML team and own the fraud and risk intelligence layer.
  • Build, deploy, monitor, and iterate production fraud models using transaction and behavioral data.
  • Improve approval rates, authorization decisioning, merchant underwriting, fraud detection, and chargeback outcomes.
  • Define and track fraud and risk metrics, including detection rate, false positive rate, chargeback rate, and dispute win rate.
  • Discover emerging fraud signals and attack patterns across global payment methods.
  • Partner with Engineering, Product, and Operations to embed fraud intelligence into payment flows and internal tooling.

Requirements

  • 5+ years of experience in machine learning, applied data science, or production ML.
  • Demonstrated experience building fraud models on the acquiring side of payments, such as at an acquirer, PSP, or payment facilitator.
  • Experience taking ML projects from proof of concept through production deployment.
  • Strong knowledge of authorization fraud, card-not-present fraud, friendly fraud, chargebacks, merchant risk, statistics, and feature engineering on high-volume financial data.
  • Ability to own ambiguous problems end-to-end and collaborate across Engineering, Product, and Operations.

Nice to have

  • Experience at an acquirer, ISO, PayFac, or payments infrastructure company.
  • Experience scaling MLOps pipelines, retraining schedules, and real-time monitoring systems.
  • Familiarity with card network rules, dispute workflows, fraud liability frameworks, and real-time fraud scoring.
  • Experience as an early or sole ML hire, or with stablecoin, crypto, and alternative payment rails.

Culture & Benefits

  • Opportunity to build core fraud and risk infrastructure during a rapid growth phase.
  • Competitive compensation with performance bonus and meaningful ownership.
  • Health and wellness benefits.
  • 401(k) savings plan and flexible time off.
  • Collaborative and innovative work environment with direct impact on company direction.

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