Remote opportunity at
MercuryStaff Data Scientist - Credit and Lending ML
Mercury seeks a remote Senior or Staff Data Scientist specializing in Credit and Lending ML to create financial infrastructure for growing companies and startups. The employer…
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About This Role
Mercury seeks a remote Senior or Staff Data Scientist specializing in Credit and Lending ML to create financial infrastructure for growing companies and startups. The employer utilizes data sources like financial reporting, payroll, and bank transactions to extend credit to businesses. In this position, the professional will develop and oversee the inference layer for the small business lending initiative, launch models into production alongside monitoring and documentation, and collaborate with…
Job Description
Mercury seeks a remote Senior or Staff Data Scientist specializing in Credit and Lending ML to create financial infrastructure for growing companies and startups. The employer utilizes data sources like financial reporting, payroll, and bank transactions to extend credit to businesses.
In this position, the professional will develop and oversee the inference layer for the small business lending initiative, launch models into production alongside monitoring and documentation, and collaborate with Product and Credit departments to establish lending strategies.
Total rewards for this role include a base salary, stock options or RSUs, and benefits. Base pay ranges from USD 166,600 to 298,800 per year for United States employees and CAD 157,400 to 282,400 per year for Canadian employees, with exact offers determined by expertise, experience, geographic location, and internal equity.
Responsibilities
- Build and maintain models for transaction classification, recurring inflow and outflow detection, annual revenue estimation, seasonal forecasting, and anomaly detection
- Transform unstructured data streams into reliable assessments of business financial health
- Deploy machine learning models into production equipped with tests, observability, and monitoring
- Partner with the Credit department to define underwriting policy, evaluate data requirements, and quantify uncertainty
- Work with Product to shape product characteristics including principal limits, pricing, and repayment schedules
- Evaluate the impact of predictive modeling on underwriting performance
- Establish technical standards for machine learning within the Credit team
Requirements
- Minimum of seven years of experience building machine learning models
- Track record of implementing models that guided automated decisions involving financial risk
- Proficiency in writing production-grade Python code
- Experience with time series, forecasting, anomaly detection, and natural language processing models
- Familiarity with deep learning, transformers, and large language models
- Strong skills in SQL and data warehouse environments
- Ability to communicate complex model mechanics to engineers, product managers, credit officers, and model validators
Qualifications
- Quantitative degree or an equivalent demonstrated background
- Direct modeling experience utilizing bank transaction data
- Background in small business lending or business credit cards
- Familiarity with merchant cash advances, revenue-based financing, or comparable offerings
Core Skills
Benefits
- Base salary
- Equity in the form of stock options or RSUs
- Benefits package as part of total rewards
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Is this position remote?
Yes, the posting indicates that the role is remote for employees located in the United States or Canada.
What is the salary range for this role?
For United States employees, the base salary ranges from USD 166,600 to 298,800 per year. For Canadian employees, the range is CAD 157,400 to 282,400 per year. Total rewards also include equity and benefits.
What experience level is required?
Candidates must have at least seven years of experience building machine learning models, along with experience implementing models that drove automated financial decisions.
Sample Interview Questions
AI-generated questions tailored to this specific role — a preview of the full practice set.