Data Scientist I - Full Stack Management Trainee

Mulligan Funding • San Diego, CA

2d • $90,000 - $107,300 • Onsite

About The Position

Headquartered in San Diego, Mulligan Funding serves as a leading provider of working capital (Up to $10M) to the small and medium-sized businesses that fuel our country. Since 2008, we have prided ourselves on our collaborative, innovative, and customer-focused approach. Enjoying a period of unprecedented growth, driven by the combination of cutting-edge technology, human touch, and unwavering integrity, we are looking to add to our people first culture, with highly motivated and results-oriented professionals, to push the limits of what’s possible while creating value for all of our partners.
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.

Requirements

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

Responsibilities

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level