In the 1950s, Norman Borlaug embarked on an effort to breed a new type of wheat that was disease resistant and had higher yields. In the outskirts of Mexico City, he combined his background of agricultural research and theoretical knowledge with careful experimentation and diligent data collection to run over 6,000 experiments - and he was ultimately successful, kicking off the “Green Revolution” that increased global crop yields by an estimated 44% and earned him a Nobel Prize. 

At Mercury, we’re building the future of financial infrastructure for startups and growing businesses. As part of our fast-growing Credit team, you’ll help build the foundational models, systems, and strategies that shape how credit decisions get made across our platform. Your work will directly influence our underwriting, risk, and credit operations — and be deployed into production to drive real outcomes.

This is a rare opportunity to get in early on a high-impact ML role with massive whitespace, broad cross-functional exposure, and deep business influence.

Here are some things you’ll do on the job:

• Own the design and development of ML and statistical models across the credit lifecycle:
• Underwriting & Risk Scoring
• Exposure Estimation & Line Assignment
• Portfolio Monitoring & Early Risk Detection
• Build production-grade models that comply with fairness, explainability, and regulatory standards, including adverse action, model documentation, and bias testing
• Partner with Credit, Product, Eng, Risk, and Ops to define and evolve credit policies, risk strategies, and approval logic
• Identify and derive high-signal features from third-party credit data (e.g., bureaus, open banking, accounting systems, revenue intelligence) and Mercury’s internal signals
• Design modeling infrastructure alongside our ML & GenAI engineering team as we build Mercury’s new ML platform
• Be a thought partner in credit strategy — proactively surfacing opportunities to expand access while managing risk

You should:

• Have 7+ years of experience in data science, ML, or analytical roles, with 2+ years in credit, credit risk, or lending
• Bring experience from fintechs, traditional banks, or card issuers — especially with B2B credit products like working capital lines, charge cards, or revolving credit (consumer lending experience is a plus)
• Understand credit risk modeling techniques: scorecards, supervised ML (e.g. logistic regression, gradient boosting), time series forecasting, portfolio monitoring
• Have built and shipped production-grade ML models in regulated environments, with a deep understanding of explainability, fairness, and compliance constraints
• Are fluent in SQL and Python, and familiar with data platforms like dbt, Spark, Airflow
• Are comfortable working with noisy, sparse, or proxy data, especially in the context of early product development
• Can operate independently, navigate ambiguity, and prioritize work for long-term impact

The total rewards package at Mercury includes base salary, equity (stock options), and benefits. Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate’s experience, expertise, geographic location, and internal pay equity relative to peers.

Our target new hire base salary ranges for this role are the following:

• US employees (any location): $200,700 - 250,900 USD
• Canadian employees (any location): CAD 189,700 - 237,100

Mercury is a financial technology company, not a bank. Banking services provided through Choice Financial Group, Column N.A., and Evolve Bank & Trust, Members FDIC.

Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic. We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.

We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on January 22, 2024. Please see the independent bias audit report covering our use of Covey here.

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