Sunbit builds financial technology for real life.
Our technology eases the stress of paying for life’s expenses by giving people more options on how and when they pay. Founded in 2016, Sunbit offers a next-generation, no-fee credit card that can be managed through a powerful mobile app, as well as a point-of-sale payment option available at more than 16,000 service locations, including auto dealership service centers, optical practices, dentist offices, veterinary clinics, and specialty healthcare services.
Sunbit was included on the 2022 Inc. 5000 list.
The financial technology company has also been named a Most Loved Workplace®, Best Point of Sale Company, and a Top Fintech Startup by CB Insights. We use cutting-edge innovations in financial technology to bring leading data and features that allow individuals to be qualified instantly, making purchases at the point of sale fast, fair, and accessible for consumers from all walks of life. We create value focused on our core values; we work tirelessly to ensure that Sunbit becomes available to everyone, everywhere.
We invite you to #UnleashYourCuriosity and join our ever-growing R&D organization.
What You’ll Do:
Sunbit is looking for an experienced, independent team player who has great data & computer science skills, a passion for data, and excellent analytical and algorithmic skills.
This role is diverse, encompassing AI/ML, data analysis, and backend engineering.
You will play a crucial role within a mission-critical team responsible for managing the heart and brain of Sunbit’s primary product. This involves working on core systems, such as POS underwriting models, models for merchant operations, and more.
You will participate in cutting-edge risk management systems that safeguard the loan product's financial operation, as well as operational systems, with a direct impact on its financial success.
Our AI/ML team is part of the R&D group, so you will work closely with engineers and product managers as well.
Key Responsibilities:
Research and develop statistical behaviors, study domain-specific data.
Develop state-of-the-art machine learning models end to end, including development, deployment, and continuous improvement. Both in-weight learning and in-context learning, for risk / operations related projects. This includes integrating models into production services and ensuring compliance with regulatory processes (e.g., using SHAP values for model explainability and providing evidence for production model audits).
Operate backend infrastructure for training and deploying ML models, ensuring optimal performance and reliability.
Develop and maintain Python code for translating ML model outputs into financial decisions.
Conduct analytical research on our model’s impact on the portfolio.
Strategize and implement changes to enhance portfolio performance.
Requirements:
- B.Sc or preferably M.Sc in quantitative discipline (preferably in Data Science, Computer Science, Mathematics, Statistics, or another related field with a strong emphasis on quantitative analysis).
- 3+ years of experience in developing and deploying ML models in a production environment, or demonstrated exceptional talent with a relevant B.Sc. degree.
- Knowledge of Data Science techniques, algorithms, and processes.
- Excellent analytical and algorithmic skills. Being able to infer conclusions and creatively offer solutions based on data analysis.
- Strong ownership and independence skills. Must thrive as the sole ML expert in a squad, comfortable taking ownership over the full life cycle of models and integrating versatile tasks (ML, data analysis, and Backend).
- Excellent teamwork skills.
- Effective communication skills to explain complex topics in English.
Recruitment Fraud Disclaimer
We’ve been made aware of fraudsters impersonating Sunbit employees during the hiring process. Please note that all official communication will come from an @sunbit.com email address, through our applicant tracking platform @sunbit.comeet-notifications.com or directly via LinkedIn. We will never ask for your age, Social Security number, bank account details, payment of any kind, or other unrelated personal information during the application process. Our hiring process always includes interviews, either by phone, zoom, or in person, before any offer is made. If something feels suspicious, please contact us at
[email protected] to confirm. We ask that you contact
[email protected] only about potential instances of fraud.
[email protected] does not reach our recruiting team directly.
Your application directly through the posting is the best way to ensure that your candidacy is reviewed by our team. Due to the volume of applications, we will not respond to nor forward emails about your candidacy that are sent to [email protected] directly, and your email about your application will be deleted from our systems.