Data Science Graduate 2027 Summer Intern

About the role

Citizens is seeking Data Science Graduate Interns for a 10‑week summer internship program. Interns will split their time between a host team within the data & analytics community—working on statistical modeling, machine learning, natural language processing, computer vision, artificial intelligence, advanced analytics, or related areas—and a cross‑functional team collaborating on a real‑world project that spans the full project cycle. Interns will work in a hybrid model from one of Citizens’ headquarters in Columbus, OH; Johnston, RI; or Boston, MA.

Experience during the program

The program offers a dual experience: half of the time is spent on ongoing work with a host team aligned to the intern’s education and interests, and the other half on a cross‑functional project with other Data & Analytics interns, colleagues, and business partners. Past projects have focused on enhancing the customer experience, optimizing business spend, identifying new market opportunities, providing business insights, model development, and engineering metrics & dashboarding.

Responsibilities

• Collaborate with business partners and mentors to understand project goals, business needs, and available data sources.
• Participate in the data preparation process, including attribute selection, exploratory data analysis (EDA), data transformation, and working with temporal data structures.
• Analyze both structured and unstructured data to uncover trends, patterns, and actionable insights.
• Apply statistical techniques such as hypothesis testing, model development, and validation to align solutions with business objectives.
• Conduct hands‑on analysis using text mining, quantitative methods, and operational data techniques.
• Incorporate feedback from stakeholders to iteratively refine models and approaches for maximum business impact.
• Present findings and recommendations to peers and business leaders as part of a capstone presentation.

Basic Qualifications

• Successfully complete a video interview assessment within 4 days of receiving the link; otherwise the application will be withdrawn.
• Currently enrolled in a graduate program (Master’s or PhD) in Statistics, Data Science, Mathematics, Economics, Analytics, Computer Science, or a related field.
• Expected graduation between December 2027 and Spring 2028 for Master’s students, or be concurrently enrolled in a PhD program.
• Minimum GPA of 3.0.
• Education in statistical theory for creating robust statistical models and analytic outputs.
• Experience working with raw and prepared datasets, with the ability to clean and process data effectively.
• Proficiency with statistical or machine‑learning tools: SQL, Python, Pandas, Jupyter Notebooks, and experience with cloud environments (AWS, Azure, or GCP).
• Strong attention to detail, ability to work independently, and manage time effectively in a fast‑paced environment.
• Valuing Diversity and Inclusion: respects individual differences, appreciates diverse cultures, values, beliefs, opinions, and generational perspectives, and embraces the value of all human differences.

Preferred Qualifications

• Team Collaboration: demonstrated ability to thrive in a team environment and collaborate with colleagues from diverse backgrounds and business units.
• Communication Skills: strong written and verbal communication, able to explain analytical findings and business insights to non‑technical stakeholders.
• Analytical Thinking: solid reasoning and problem‑solving skills, capable of breaking down complex problems using logic and quantitative methods.
• Curiosity & Initiative: proactive in asking thoughtful questions, researching unfamiliar topics, and seeking clarity on project goals.
• Resilience & Drive: persistence and tenacity to work through challenges, adapt to feedback, and stay focused on delivering results.
• Business Data Analytics: ability to collect, identify, analyze, and interpret business data using various techniques and an understanding of business data analysis concepts.
• Familiarity with tools such as Redshift, Snowflake, Amazon S3, and Amazon SageMaker.

Schedule

Hours per week: 40

Work schedule: Monday – Friday, 8:30 am – 5:00 pm