Develop and deploy machine learning models, design experiments and A/B tests, productionalize data science code with GitHub and MLOps pipelines, and collaborate with data vendors. The role offers hands-on experience with cloud infrastructure, advanced machine learning tools, and production AI systems while working alongside senior engineering and data science leaders.
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.
You will:
- 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.
Qualifications & Requirements
- 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.
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What you need to know about the Los Angeles Tech Scene
Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
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- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
