Data Science Internship (Summer 2026)

Mine
New York CityPosted 27 March 2026

Job Description

Data Science Internship (Summer 2026) ABOUT US We are solving one of the most critical problems society faces today: A decline in financial optimism amongst young adults. Financial literacy has dropped to a 3-decade low. Only 8% of Americans are confident in their ability to make financial decisions. Fewer and fewer believe they’ll match or exceed the financial status of their parents. Enter Mine: The AI Personal Finance Company. We put a financial ally and the tools for financial success in the pocket of every young adult. Today, we help over 1,000,000 users confidently build credit, become personal finance experts, and find line of sight to financial independence. We’re backed by Kleiner Perkins, SV Angel, Y Combinator, and the founders of eight Unicorns, including Postmates, Public, and Checkout.com http://Checkout.com. In 2025, Mine raised a yet-to-be-announced Series A from top-tier investors to double down on our growth. We've built tools that are top-tier, easy as #$^% to use, and designed to empower our users to reach financial greatness: MoneyGPT: The world's leading AI Money Advisor. Connect your accounts and get personalized insights, alerts, and advice—tailored to your goals, not generic tips. The Mine Card: The first debit card that builds credit. The good parts of a credit card (build credit, awesome rewards) and the easy parts of a debit card (pays itself off daily, can’t spend more than you have in your bank account). We don’t charge interest or hidden fees. Mine Learn: Duolingo-style financial literacy lessons to learn about everything from insurance to inheritance tax. Mine Track: The easiest track and budgeting tool you’ve ever used. MoneyGPT insights + best-in-class charts for total clarity on your spending and credit. And lots more on the roadmap… THE JOB We need a data person who wants to do all of it. As our Full Stack Data Science Intern, you won't be cleaning CSVs in a corner. You'll own real projects end to end, from scoping requirements with stakeholders to shipping dashboards and pipelines that the team actually relies on. Mine is building the intelligence layer on top of your financial life. Our data platform powers everything from MoneyGPT to fraud detection to growth analytics. You'll help keep that platform healthy, build on top of it, and make it better. This role starts as a summer internship with the opportunity to continue part-time into the school year and convert to full-time. If you want to be a full-stack data professional who touches everything from data extraction to ML engineering, this is the place to start. We value in-person work in NYC. It helps us move faster, build genuine friendships, and get stuff done. We support relocation! If you're unable to move to NYC and are still crazy about Mine, apply anyway. WHAT YOU'LL DO 1. Own data projects end to end: gather requirements, design solutions, get stakeholder buy-in, and ship 2. Build and maintain dashboards that track product performance across Mine Card, MoneyGPT, and new launches 3. Monitor and maintain data pipelines (data integration and analytics engineering), ensuring data quality and platform reliability 4. Explore and prototype ML/AI solutions that automate decisions across the business, from credit risk signals to marketing optimization to product recommendations 5. Suggest and implement best practices to improve our data infrastructure 6. Collaborate directly with engineering, product, and business stakeholders to inform decision with Data. WHAT YOU HAVE 1. Experience with SQL and at least one programming language (Python preferred) 2. Familiarity with data tools like dbt, BigQuery, Lightdash, or similar (you don't need all of them) 3. A full-stack mindset: you're excited to work across extraction, transformation, analytics, visualization, and even ML and AI 4. Strong agency: you follow up without being asked, communicate blockers early, and find the next thing to do on your own 5. Comfort figu ... (truncated, view full listing at source)
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