Senior Applied Data Scientist

Clair; New York (NY); Hybrid; USD 190,000 - 200,000; Full time

Benefits offered by this job

Medical, Dental, & Vision Coverage

Fully-paid parental leave

Company-sponsored 401k, HSA, and FSA

Unlimited vacation for salaried roles

Work from home setup allowance

Access to your earnings every day onCl

Disability insurance

Job summary

Clair, a fintech employer in New York, seeks an Applied Data Scientist to develop and maintain credit models powering underwriting and decision systems. You will design predictive features from transaction data, forecast income flows, spending, and repayment behaviors, and collaborate with engineering to deploy models in production.

The role blends risk modeling with feature engineering, deploying production-ready ML models, and communicating insights to stakeholders across product and risk

Qualifications

• 5+ years of professional experience in data science and machine learning.
• Experience building and productionizing credit or risk assessment models.
• Strong proficiency in Python and familiarity with modern ML libraries (TensorFlow, PyTorch, XGBoost, etc.).
• Strong command of SQL and experience working with large transactional and time-series datasets.
• Strong communication skills and ability to translate complex findings into actionable insights.
• Experience working with cross-functional teams in a fast-paced production environment.

Responsibilities

• Develop and maintain credit risk and repayment models that directly power Clair’s underwriting and decision systems.
• Design and engineer predictive features using transaction-level data, including the prediction of user income flows, spending, and repayment behaviors.
• Collaborate with engineering teams to deploy, monitor, and optimize models in production environments using AWS and Snowflake ML Platform.
• Build prototypes of new modeling methodologies and present them to stakeholders for evaluation and feedback.
• Investigate and analyze credit performance, identifying root causes of model drift or unexpected repayment behavior.
• Partner cross-functionally with product, risk, and engineering teams to turn data insights into product improvements and credit strategy refinements.
• Communicate technical concepts clearly to both technical and non-technical audiences.
• Stay current on best practices and emerging techniques in credit modeling, explainable AI, and financial ML systems.

Skills

Python

SQL

Machine learning

Communication

Cross-functional collaboration

Tools

TensorFlow

PyTorch

XGBoost

AWS

Snowflake ML Platform

Job 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 an Applied Data Scientist on Clair’s Data Science team, you’ll be responsible for developing and maintaining the next generation of credit models and predictive systems that power Clair’s financial products. You’ll shape how millions of hourly workers access affordable credit, leveraging cutting‑edge data science to assess risk, predict repayment, and optimize credit decisions.

We’re looking for someone who thrives at the intersection of data science, machine learning, and fintech, and who’s excited to translate messy, real‑world data into clear, actionable intelligence. This role blends credit modeling with feature engineering — from designing new model features (including predictive features) based on user transaction data to deploying and monitoring production‑ready ML models that drive critical product decisions.

Key Responsibilities

• Develop and maintain credit risk and repayment models that directly power Clair’s underwriting and decision systems.
• Design and engineer predictive features using transaction‑level data, including the prediction of user income flows, spending, and repayment behaviors.
• Collaborate with engineering teams to deploy, monitor, and optimize models in production environments using AWS and Snowflake ML Platform.
• Build prototypes of new modeling methodologies and present them to stakeholders for evaluation and feedback.
• Investigate and analyze credit performance, identifying root causes of model drift or unexpected repayment behavior.
• Partner cross‑functionally with product, risk, and engineering teams to turn data insights into product improvements and credit strategy refinements.
• Communicate technical concepts clearly to both technical and non‑technical audiences.
• Stay current on best practices and emerging techniques in credit modeling, explainable AI, and financial ML systems.

Minimum Qualifications

• 5+ years of professional experience in data science and machine learning.
• Proven track record of leading end‑to‑end data science projects — from research and model development to deployment and monitoring.
• Experience building and productionizing credit or risk assessment models.
• Strong proficiency in Python and familiarity with modern ML libraries (TensorFlow, PyTorch, XGBoost, etc.).
• Strong command of SQL and experience working with large transactional and time‑series datasets.
• Strong communication skills and ability to translate complex findings into actionable insights.
• Experience working with cross‑functional teams in a fast‑paced production environment.

Preferred Qualifications

• Experience in fintech or credit risk modeling.
• Experience with cloud‑based machine learning environments (AWS, Azure, Snowflake ML Platform, etc.).
• Familiarity with model explainability techniques and compliance requirements in financial modeling.
• Experience working with time‑series analysis and modeling, including forecasting, trend detection, and temporal feature engineering.

Location

This is a hybrid position based in 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.

Compensation

The annual base salary for this role is $190,000-$200,000. 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.

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:

Benefits

• 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

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 [e-mail]