Data/Analytics Co-op

Later is the world’s most intelligent influencer marketing company, built to give brands the confidence to create unforgettable campaigns. By combining real creator relationships, trusted intelligence, and expert guidance, Later removes fear and guesswork from one of marketing’s most visible investments. Built on a native, AI-powered platform and more than a decade of proprietary data—including billions of social interactions, impressions, and $2.4B+ in verified influencer-driven purchases—Later helps teams understand what will work before they launch. By combining trusted insight with expert guidance, Later removes guesswork from influencer marketing, enabling brands to choose the right creators, execute fully managed campaigns, and drive meaningful growth across awareness, engagement, and revenue. Trusted by leading enterprise brands including Nike, Wayfair, Unilever, and Southwest Airlines, Later bridges creativity and performance so campaigns don’t just look good—they deliver results. Learn more at later.com . About this position: We're looking for a Data / Analytics Co-op to join our Data team and gain practical experience building the data models and analytics foundations that help teams across Later make better decisions. You'll work alongside Data Engineers, Analytics Engineers, and Analysts to transform raw data into reliable, well-structured datasets that power reporting, dashboards, product analytics, and business decisions. You'll contribute to real projects using technologies such as SQL, dbt, BigQuery, Python, and business intelligence tools . What you'll be doing Build and maintain SQL and dbt data models that transform raw data into reliable, analytics-ready datasets. Create reusable datasets and metrics that support consistent reporting and self-service analytics across teams. Build data quality tests and investigate issues to improve the accuracy and reliability of our data. Partner with Analysts and business teams to translate reporting and analytics needs into clear data models and definitions. Improve existing data models and pipelines for performance, maintainability, and scalability. Contribute to documentation, data lineage, code reviews, and engineering best practices. Work with large datasets in BigQuery and gain hands-on experience with a modern cloud data platform. What success looks like Within 30 days: You've ramped up on Later's data platform, core datasets, and development workflows and are contributing to SQL and dbt projects. Within 90 days: You're independently building and testing analytics models and contributing reliable datasets used in reporting and analysis. By the end of your co-op: You've shipped meaningful improvements to our analytics platform and can take a data requirement from definition through development, testing, documentation, and delivery. You've developed a strong understanding of how to translate business questions into simple, reliable, and useful data solutions. What you bring We are committed to building an inclusive, supportive place for you to do the best and most rewarding work of your career. If you identify with any of the following, we encourage you to apply! Currently pursuing an undergraduate degree or diploma in Computer Science, Data Science, Statistics, Mathematics, Engineering, Information Systems, or a related technical field. Strong interest in analytics engineering, data engineering, or business intelligence. Working knowledge of SQL , relational databases, and basic data modeling concepts. Strong analytical and problem-solving skills with attention to detail. Curiosity about how data is transformed and used to support business decisions. Clear communication skills and an ability to collaborate with technical and non-technical partners. Ability to learn quickly and work effectively in a fast-paced environment. Exposure to dbt, BigQuery or other cloud data warehouses, Python, Git, or BI tools through coursework, personal projects, internships, or prior c…