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.
- 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.
A reasonable estimate of the base salary range for this role is $90,000 to $107,300 per year. In determining final compensation within the base range, Mulligan Funding considers a variety of factors, including market data, relevant experience, skills, and past performance.
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.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
