Applied ML / Data Science Intern (MS or PhD)
Applied ML / Data Science Intern (MS or PhD) at Wildcard — San Francisco, CA, US
- Company: Wildcard
- Location: San Francisco, CA, US
- Employment type: INTERN
- Salary: USD 5000–8000 / year
- Posted: 2026-07-17
About this role
About Wildcard
Wildcard is building the infrastructure layer for AI commerce. We help e-commerce brands understand how they appear across AI shopping surfaces, improve product visibility, and connect that visibility to real business outcomes. Backed by Y Combinator, Wildcard sits at the intersection of ecommerce, AI systems, and data.
About the Role
Wildcard is hiring an Applied ML / Data Science Intern to work on a range of high-impact data problems across the business. This is a role for someone currently pursuing an MS or PhD who wants to work on fast-moving, applied problems with direct product and company impact.
This internship is not centered around a single long-term research project. You’ll work across multiple efforts, often in parallel, depending on what the company needs most. That may include attribution systems, site traffic modeling, experiment design, data analysis, building pipelines to collect new data points, and helping turn messy signals into usable product intelligence.
The right person for this role has strong fundamentals in data science and machine learning, prior hands-on experience applying those skills, and enough software engineering ability to actually build. This is not a pure research role and not a pure analytics role. You should be comfortable moving between modeling, analysis, and implementation.
You’ll work closely with the founder and move quickly from question to analysis to implementation.
What You’ll Work On
Build and improve attribution systems that connect AI visibility to site traffic and downstream outcomes
Develop models and analyses around site traffic, conversion patterns, and performance trends
Design ways to collect new data points and engineer pipelines that make those signals usable
Analyze messy real-world data and turn it into clear insights for product and business decisions
Support multiple fast-moving projects at once, shifting between modeling, analysis, experimentation, and data engineering as needed
Prototype internal tools and workflows that improve how Wildcard measures performance and opportunity
What We’re Looking For
Must-Have
Currently pursuing an MS or PhD in Computer Science, Machine Learning, Data Science, Statistics, Economics, or a related quantitative field
Strong fundamentals in machine learning, statistics, and data science
Prior hands-on experience applying ML or data science in research, industry, startups, or labs
Strong Python skills
Software engineering ability beyond notebooks, including writing production-minded code, building data workflows, or implementing internal tools
Comfortable working with messy, incomplete, real-world data
Able to move between analysis and implementation
High ownership and comfort operating in a fast-paced startup environment
Strong written and spoken English
Nice-to-Have
Experience with attribution modeling, traffic analysis, forecasting, or causal inference
Experience designing data pipelines or instrumentation to collect new signals
Strong SQL skills
Experience with experimentation, product analytics, or growth analytics
Familiarity with ecommerce, marketplaces, search, or recommendation systems
Prior startup, research lab, or applied industry experience
What Makes This Interesting
You’ll work on problems that sit between modeling, product, and data infrastructure. The work is fast-paced, highly practical, and tied to real company priorities. Rather than spending months on one narrow project, you’ll get exposure to a broad set of problems and help build the systems that let us understand what is happening, why it is happening, and what to do next.
Location
In person in San Francisco
5 days a week in office