Role overview

Later is an AI-powered influencer marketing platform trusted by major brands including Nike, Wayfair, Unilever, and Southwest Airlines. The Data & Analytics team is seeking a co-op student to support the expansion and evolution of the company’s analytics capabilities. You will work directly with a Senior Analyst, contributing to the tools and processes that drive insights across the organization.

Key responsibilities

Build and maintain data sources, reports, and dashboards using tools such as BigQuery, dbt, and Vibe code applications.
Pull, validate, and structure data sets for ad hoc analysis to support business questions and client needs.
Review data for accuracy and completeness before it reaches stakeholders and other teams.
Establish automated guardrails to flag known data gaps and improve data quality awareness.
Identify and help resolve data quality issues in collaboration with the Senior Analyst and broader team.
Communicate findings and their business impact clearly to analysts and non-technical stakeholders.
Partner with the Senior Analyst to prioritize and develop scalable approaches to analytics infrastructure.

Requirements

Currently enrolled in a co-op program through Northeastern University.
Pursuing a degree in Statistics, Data Science, Computer Science, Economics, Mathematics, or a related technical field.
Experience working in BigQuery or a comparable SQL-based data warehouse.
Demonstrated ability to review and validate data sets for accuracy and completeness.
Strong written and verbal communication skills, with comfort presenting findings to both technical and non-technical audiences.
Experience with R, Python, dbt, Omni, or Domo is valued but not required.

What makes this role worth considering

You will develop direct ownership of at least one reporting area and independently troubleshoot common data issues by the end of the term. This co-op runs from January to June 2027 and requires five days per week in-office at the Boston location. You will build lasting relationships with the analytics team while creating tangible impact through improved dashboards and processes that the organization relies on.