Назад
15 часов назад

Staff Data Scientist (Credit and Lending ML)

166 600 - 298 800$
Формат работы
remote (только USA)/onsite
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US/Canada
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Мэтч & Сопровод

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Описание вакансии

Текст:
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TL;DR
Staff Data Scientist (Credit and Lending ML): Building and owning the inference layer and production ML models for small-business lending, including transaction classification, revenue estimation, forecasting, and anomaly detection, with an accent on trustworthy automated credit decisions. Focus on deploying observable and tested models, quantifying underwriting uncertainty, shaping lending products, and setting technical standards for credit ML.

Location: San Francisco, CA; New York, NY; Portland, OR; or remote within Canada or the United States. Office or remote options are available.

Salary: US employees: $166,600–$298,800 USD base salary. Canadian employees: $157,400–$282,400 CAD base salary.

Company

Mercury is a fintech company building financial infrastructure, credit, and lending products for startups and growing businesses; banking services are provided through Choice Financial Group and Column N.A.

What you will do

  • Build and own ML models for transaction classification, recurring inflow and outflow detection, annual revenue estimation, seasonal forecasting, anomaly detection, and related lending use cases.
  • Turn bank transactions, storefront sales, and other data streams into a defensible view of business health.
  • Deploy models to production with observability, monitoring, documentation, and tests.
  • Partner with Credit on underwriting policy, data collection, follow-up information, and uncertainty quantification.
  • Partner with Product on principal sizes, pricing, repayment terms, and the broader shape of the lending product.
  • Assess where predictive modeling improves underwriting and set the technical bar for ML in Credit.

Requirements

  • 7+ years of experience building ML models.
  • Experience implementing models that shaped automated decisions involving significant financial stakes.
  • Production-grade Python, strong SQL, and comfort working in a data warehouse.
  • Depth beyond classification, including time series and forecasting, anomaly detection, and NLP models.
  • Proficiency with deep learning, transformers, and LLMs.
  • Ability to explain models to credit officers, model validators, product managers, and engineers.
  • Ability to establish modeling standards for data-science colleagues.
  • A quantitative degree or equivalent expertise developed through another path.

Nice to have

  • Direct experience modeling bank transaction data.
  • Experience in small-business lending or business credit cards.
  • Experience with revenue-based financing, merchant cash advances, or similar products.

Culture & Benefits

  • Total rewards include base salary, equity through stock options or RSUs, and benefits.
  • Compensation is adjusted based on experience, expertise, geographic location, and internal pay equity.
  • Mercury values diversity and belonging and provides reasonable recruitment accommodations for applicants with disabilities or special needs.
  • Mercury is an Equal Employment Opportunity employer.

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