A Top Place to Work
We believe in small businesses and the people who grow them. At Credibly, we leverage cutting-edge data science, technology, partner relations, and customer support to provide business owners with accelerated access to right-sized capital solutions. From working capital loans and merchant cash advances to lines of credit, we offer a suite of financing products that can accommodate nearly any stage of business development or credit profile.
Founded in 2010 with offices in Michigan, New York, and Arizona, we have provided access to over $2.3 billion to more than 46,000 small businesses nationwide. On top of being nominated as one of Crain's 50 fastest growing companies in New York and making several appearances on the Inc. 500 list, Credibly was also recently named a Top 25 Lending Technology Company by The Financial Technology Report.
We invite tech-savvy college students to apply for our Paid Summer Internship Program. There are opportunities for all students entering or past their sophomore year of college.
The program offers participants hands-on experience by working alongside the company's experienced tech and data science teams to gain practical experience, develop industry-relevant skills, and make meaningful contributions to the small business community. Interns will also have the opportunity to develop their own solution through a collaborative final project.
This program features a range of internship opportunities tailored to different interests and skill sets. Applicants can review the available options below and indicate their preferences during the application process. Documents required for earning college credit will be reviewed on a case-by-case basis.
Data Science/Analyst Intern will work the summer as part of the Risk Analytics and Data Science organization, tasked with leveraging advanced analytics and statistical techniques to drive business growth and risk mitigation.
The ideal candidate is a technically adept and collaborative future professional who works closely with business partners to maintain data integrity and transparency. They have a passion for learning how to build Machine Learning and Advanced Analytics Solutions that provide seamless access to key insights.
Additionally, the role involves analyzing data to uncover business opportunities, forecast trends, and drive revenue and cost efficiencies while ensuring data trust. The intern will have an opportunity to contribute to multiple projects, generate insightful reports, and learn about analytics best practices and trends.
As a Data Science/Analyst Intern, you will help bridge the gap between complex data and strategic business decisions. Your responsibilities will include:
Through the project work involving these activities, you'll play a crucial part in ensuring that data flows smoothly and securely, empowering data-driven decision-making throughout the organization.
· Currently pursuing or holding a bachelor's degree or master's degree in a quantitative field such as Computer Science, Data Science, Statistics.
· Strong analytical, critical thinking and problem-solving skills.
· Proficiency in Python and MySQL, with hands-on experience in using Github/Bitbucket and Jira for code management and project tracking.
· Experience in or a desire to learn tools like Google Sheets for data analysis and presentation, showcasing the ability to manage and process data efficiently.
· Solid written and verbal communication skills.
· An exceptionally strong desire to take on ownership roles in projects, learn new skills, see how analytics can drive value in industry.
· Relevant experience or strong interest in Banking or Risk Management sectors.
· Solid understanding of statistical methodologies and their application in data analysis.
· Experience or interest in developing Machine Learning and AI Solutions, with the ability to apply these technologies to real-world challenges.
· Application Deadline: March 31, 2026
· Date you will hear back by: May 15, 2026
· Start Date: June 1, 2026
Description: reflects the general nature and level of work performed by employees within this classification. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities, and qualifications required of employees assigned ...
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