Data Analytics Undergraduate 2027 Summer Intern

About the role

We’re developing the next generation of Colleagues! Join the data‑driven culture at Citizens and learn how we keep customers at the center of everything we do. We are looking for interns to join our 10‑week summer internship program and support innovative data & analytics initiatives across the bank.

Experience during the program

Our program offers interns a unique dual experience – participants spend half of their time individually partnered with a host team within the data & analytics community to participate in ongoing work. Assignments for data analyst interns may be in areas aligned to advanced analytics, reporting and dashboarding, data visualization, data mining, automation, root‑cause analysis, cohort analysis, and other ad‑hoc analysis. This component provides direct exposure to teams in areas that align to intern education and interests.

The other half of the time, interns work on a cross‑functional team, collaborating with other Data & Analytics interns, colleagues, and business partners to work on a real‑world project. Projects are tailored so interns can experience the full project cycle. Past projects have centered on enhancing the customer experience, optimizing business spend, identifying new market opportunities, providing business insights, model development, and engineering metrics & dashboarding.

Interns are expected to adopt a hybrid work structure and work out of one of our headquarters in Columbus, OH, Johnston, RI, or Boston, MA.

Responsibilities

• Work with business partners and mentors to review the business question, project objectives, available data, and gather requirements to determine the best analytical approach.
• Work within our data repositories to assemble, manage, and investigate relevant data.
• Quantify information and sort it for analysis, investigate and highlight trends.
• Collect, identify, analyze, and interpret business data to enable strategic decision‑making for business needs and requirements.
• Learn the pros and cons of different approaches, tools, techniques, and methodologies.
• Effectively communicate with cross‑functional partners and internal teams to deliver solutions in a timely fashion, using storytelling to present data persuasively.
• Gain feedback from partners and iteratively fine‑tune an approach to resolve the question and maximize business impact.
• Present contributions to colleagues and business leaders as a capstone exercise.

Requirements

Basic Qualifications

• Successfully complete a video interview assessment within 4 days of receiving the link.
• Currently pursuing a bachelor’s degree in Data Analytics, Statistics, Mathematics, Economics, Finance, Computer Science, or a related quantitative field.
• Expected graduation date between December 2027 and Spring 2028.
• Minimum GPA of 3.0.
• Experience working with structured and unstructured datasets, including data cleaning, transformation, and exploration.
• Demonstrates appreciation for varied backgrounds, experiences, and viewpoints; encourages open collaboration.
• Permanent work authorization in the United States (no CPT, OPT, or visa sponsorship).

Preferred Qualifications

• Technical familiarity or interest in tools such as Amazon Redshift, Snowflake, Amazon S3, and Alteryx (prior experience a plus).
• Eagerness to learn from mentors and business partners, growing technical and business acumen through hands‑on project work.
• Proven ability to thrive in a team environment and collaborate effectively with colleagues from diverse backgrounds and business units.
• Strong written and verbal communication skills; ability to explain analytical findings and business insights to non‑technical stakeholders.
• Solid analytical reasoning and problem‑solving skills; ability to break down complex problems using logic and quantitative methods.
• Curiosity and initiative; proactive in asking thoughtful questions, researching unfamiliar topics, and seeking clarity on project goals.
• Resilience and drive; persistence in working through challenges, adapting to feedback, and staying focused on delivering results.

Work Schedule

• Hours per Week: 40
• Work Schedule: Monday – Friday, 8:30 am – 5:00 pm