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Data Science Co-op

🏢 Later · 📍 Vancouver, British Columbia, Canada
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Position Summary & Responsibilities

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:

Later is looking for a full-time co-op starting January 2027 to help support the product team; you will be working on new product features and having a meaningful impact on the company. If you enjoy tackling challenges, learning about new technologies, thinking of creative solutions, and sometimes blazing a new trail, we want to talk to you. This position is the perfect opportunity for you to learn and grow. This will be an 4-month term with a potential of extension.  

Technical Qualifications:

  • In the 3rd year of statistics, computer science, math, physics, economics, or other technical undergraduate program; consideration may be given to graduate students as well. Creative thinker, fast learner, good grades. 
  • Strong coding ability in R and/or Python, passionate about data science and the technology industry. Some experience with SQL is a plus.
  • Experience with and technical understanding of statistical modeling & machine learning techniques.
  • Experience with big data/deploying models into production is a plus (Spark, AWS, Docker, Flask, plumber).
  • A passion for social media (Instagram, TikTok, Pinterest, etc.) is a big plus.

We are committed to building an inclusive, supportive place for y

🎯 Candidate Preparation Guide For Later Applicants

Key Role Competencies & Evaluation Highlights

Key Role Focus:

Measuring deep domain expertise in social media marketing ecosystems, creator economies, and product-led growth (PLG) loops.

📋 Preparation Priorities (Key Areas to Clarify):
  • 1. Viewing social media purely as broadcast media rather than interactive community building
  • 2. Relying on outdated marketing playbooks that ignore current creator economy trends
  • 3. Showing weak understanding of SaaS freemium to paid conversion funnels
✨ Recommended Role Alignment Hook:

I scale social media tech platforms by engineering product-led growth loops that turn casual creators into lifelong subscribers.

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