Data Scientist I - Full Stack Management Trainee

Mulligan Funding is a San Diego based provider of funding to the Small and Medium Sized Business market. We are building a deeply researched and first-of-it’s-kind, Agentic AI complete funnel automation strategy. Mulligan has decades of deep credit underwriting and analytics expertise, combined with rich data from almost a million applications and billions of dollars funded via a wide loan size of $10k to $10 million. We are a mission-driven company, focused on solving the SMB market’s access to the fast and affordable capital they need to thrive by re-inventing how credit risk is measured, priced, and negotiated. We combine a generational-technology with unwavering integrity and a human touch.

At Mulligan, we are transforming small business lending by replacing legacy processes with fast, intelligent, AI-driven decisioning. Backed by 18 years of proprietary credit data and deep risk expertise, our production-grade AI agents are already running in active credit and underwriting workflows. As we expand this AI-first approach across Sales, Customer Lifecycle, Finance, and Capital Markets, we offer an uncommonly rich environment for emerging data scientists. 

By stepping directly into the center of these efforts, you won't just observe modern machine learning—you will gain hands-on experience with advanced, industry-leading tools and complex technical architectures while contributing directly to our mission of scaling AI across the organization.

The Data Scientist I - Full Stack Management Trainee role focuses on machine learning development, model deployment, and MLOps. Working alongside senior engineering and data science leads, you will take ownership of model construction, experimental design, pipeline development, and code productionalization on cloud infrastructure, making an immediate impact on our production systems.

• Assist in constructing, testing, and deploying machine learning models.
• Design and evaluate experimental designs and A/B testing methodologies.
• Productionalize data science code utilizing GitHub, version control, and modern MLOps pipelines.
• Work with data vendors in pushing data boundaries.

• Education: Master’s degree or higher in Mathematics, Statistics, or a Quantitative field.
• Statistical Expertise: Hands-on experience with A/B testing methodologies and experimental design.
• ML & Engineering: Proven experience building ML models and exposure to MLOps principles.
• Production Skills: Ability to productionalize code using GitHub and manage code versioning.

Mulligan Funding is an Equal Opportunity Employer (EOE) and takes great pride in building a diverse work environment. Qualified applicants are considered for employment without regard to age, race, religion, gender, national origin, sexual orientation, disability or veteran status.