Imprint is reimagining co-branded credit cards & financial products to be smarter, more rewarding, and truly brand-first. This role provides hands-on experience in developing data-driven solutions that support smarter and safer credit decisions.
Requirements
- Coursework or project experience with Python (pandas, scikit-learn, NumPy) and SQL.
Responsibilities
- Design, develop, and test statistical and machine learning models for credit risk areas (underwriting, fraud detection, portfolio management).
- Explore large datasets, identify patterns, and contribute to insights that inform credit strategies.
- Help track how models perform over time, assist with validation, and support documentation to ensure compliance with governance and regulatory standards.
- Partner with cross-functional teams (Product, Engineering, Credit) to see how risk data science connects with product development and business strategy across the company.
- Take on meaningful projects, receive mentorship from experienced data scientists, and build presentation skills by sharing your work with team members and senior leaders.
Other
- Currently pursuing a Bachelor’s or Master’s degree in a quantitative field (Statistics, Mathematics, Computer Science, Economics, Engineering, etc.).
- Interest in statistics, machine learning, and problem-solving.
- Excellent communication skills, both written and verbal, with a customer-focused mindset.
- Eagerness to learn, collaborate, and take on new challenges.
- This role will be a hybrid work format, with time split between working remotely and working onsite from our New York HQ, 2-3 days a week as required by your manager.
