Machine Learning Engineer - Financial Data at Clair

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

12 Mar, 26

Salary

200000.0

Posted On

12 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning Engineering, Data Science, Data Engineering, Feature Engineering, Python, SQL, ML Frameworks, Production ML Pipelines, Cloud Environments, Data Modeling, Forecasting, Statistical Analysis, Communication Skills, Software Engineering, Credit Risk Modeling, MLOps Tools, Fintech

Industry

technology;Information and Internet

Description

About Clair If you can send your friends money in seconds, why does it still take your employer two weeks to send your paycheck? At Clair, we are on a mission to create financial freedom for America's workers by giving them a digital banking platform that allows them to get paid as soon as they clock out of work. But we're not just another digital bank or on-demand pay provider. We meet Americans at their place of work by embedding our products within the scheduling, workforce management, and payroll apps they already use every day. Learn more about us at getclair.com/about About the Role As a Machine Learning Engineer on Clair’s Data team, you will be responsible for transforming diverse financial data sources, including but not limited to Plaid transactions, into production-grade features, predictive signals, and modeling pipelines that power Clair’s credit and underwriting systems. Your work will focus on building the core feature layer that our credit models depend on: extracting structure from messy financial data, designing robust predictive features, forecasting key user-level events (such as income timing or financial stability indicators), and ensuring that these features are efficiently deployed, monitored, and continuously improved. In addition to hands-on modeling and feature engineering, you will contribute to the development of Clair’s Data Science platform – building tooling, automation, and infrastructure that make it easier to train, deploy, and monitor ML systems at scale. This role is ideal for someone who loves crafting meaningful features out of raw data, scaling ML systems in production, and driving the technical foundations of a modern financial ML stack. Key Responsibilities Engineer high-quality features from financial and behavioral data to support credit modeling. Build and maintain scalable pipelines for feature computation, income detection, and financial signal extraction. Develop forecasting and predictive models for income timing, user stability, and financial behavior patterns. Deploy, monitor, and optimize ML models and feature pipelines in production using AWS, Snowflake, or other tooling. Contribute to the development of Clair’s Data Science platform, including model deployment workflows, feature stores, and monitoring systems. Collaborate with engineering, product, and risk teams to understand their workflows and ensure data products have high availability for their use cases Prototype new modeling techniques and evaluate their impact on credit and underwriting performance. Communicate findings and technical decisions clearly to both technical and non-technical stakeholders. Qualifications 5+ years of experience in machine learning engineering, data science, data engineering, or a related technical field. Strong experience in feature engineering, particularly with large-scale transactional or time-series datasets. Proficiency in Python, SQL, and modern ML frameworks (e.g., PyTorch, XGBoost, sci-kit learn). Experience building production ML pipelines and deploying models in cloud environments Strong understanding of data modeling, forecasting, and statistical analysis. Clear and effective communication skills when working with product, engineering, and business stakeholders. Demonstrated ability to execute end-to-end: from raw data exploration to production ML implementation. Software engineering proficiency with a sensible adherence to good software design patterns Things We Consider a Plus Experience with Plaid or similar financial data providers. Background in credit risk modeling, underwriting features, or financial signal extraction. Familiarity with MLOps tools (e.g., MLflow, SageMaker, Feature Stores, Airflow). Experience building or contributing to internal Data Science platforms. Knowledge of explainable ML techniques and regulated-model requirements. Prior work in fintech, credit, or payments. Additional Details Location: This is a hybrid position based out of New York City, you will be expected to come into the office at least three days a week (Tuesdays, Wednesdays, & Thursdays) with additional days on occasion for client meetings. We’re open to remote candidates whose experience and background strongly match the requirements of the role. Compensation: The annual base salary for this role is $200,000 for NYC and SF-based candidates. The base pay for this role is determined using many factors, such as education, skills and experience and is reflective of Clair Series stage and size. Base pay is only one part of Clair’s competitive total compensation package which includes equity, benefits and additional perks. The base pay range is subject to change and may be modified in the future. Clair will only contact candidates from @getclair.com email addresses. We will never ask for payments or sensitive personal information during the hiring process. If you happen to receive anything suspicious, please ignore it. Need more convincing? Apart from getting to work with our incredible team, here are some of the benefits you can expect when you join Clair: Medical, Dental, & Vision Coverage, with option to extend to your family Fully-paid parental leave Company-sponsored 401k, HSA, and FSA Unlimited vacation for salaried roles, generous PTO for hourly roles Work from home setup allowance Access to your earnings every day on Clair Company-sponsored short-term and long-term disability insurance Equal Opportunity Employer Information Clair is an equal opportunity employer and we value diversity at our company. We actively seek a diverse applicant pool and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. For questions, please email us at careers@getclair.com

Responsibilities

Engineer high-quality features from diverse financial data sources to support credit modeling and build scalable pipelines for feature computation. Collaborate with various teams to ensure data products are available for their use cases and prototype new modeling techniques.