Data Science Co-op, July 2025 - job 1 of 2

As a Data Science Co-op at Jellyfish, you'll work on developing algorithms that analyze how software developers engage with code, documentation, and collaboration. You'll also contribute to blog posts that discuss your discoveries in developer practices, learn to create machine learning models, and present analyses that help our clients comprehend their development processes more effectively.

Ideal candidates for the Data Science Co-op at Jellyfish should have a solid foundation in programming, regardless of the language. A passion for working with real-world data and an eagerness to learn and teach others is crucial. Prior internship or co-op experience is preferred, and experience with Python libraries like pandas or scikit-learn is a plus.

Joining as a Data Science Co-op at Jellyfish not only provides hands-on experience in data science and machine learning, but also allows you to work alongside industry leaders. You'll gain valuable insights into real-world applications of technology that can significantly bolster your resume and open doors for future opportunities.

At Jellyfish, our work environment is collaborative, fun, and challenging. We prioritize teamwork and it’s common to see humor integrating into our day-to-day. You'll be part of a tight-knit team, making meaningful contributions while learning from seasoned entrepreneurs in the tech landscape.

The Data Science Co-op program at Jellyfish is set for July 2025. Candidates must be authorized to work for any employer in the U.S., as we’re unable to sponsor any employment visas at this time. Looking for driven, dedicated individuals who are ready for a unique opportunity to grow!

When answering this question, you should speak to your passion for turning data into meaningful insights, and your enthusiasm for product development. Share how Jellyfish’s mission resonates with you and how you see yourself contributing to innovative solutions.

Be prepared to discuss a specific project, outlining your role, the methodologies you employed, and the outcomes. Highlight your analysis, any challenges faced, and how you overcame them, focusing on your critical thinking and problem-solving skills.

Mention your favorite learning techniques, whether that's hands-on projects, online courses, or collaborative coding. Emphasize your eagerness to adapt and learn something new, perhaps even sharing a recent experience of picking up a new skill.

Discuss traits like communication, collaboration, and a positive attitude. Provide examples of situations where these qualities helped you contribute to a team's success, illustrating your ability to connect with others.

Use this opportunity to walk through a specific example where your analysis directly impacted a project. Discuss your methodology, the tools used, and how the insights were communicated to stakeholders for effective decision-making.

Explain your system for prioritization, which could include task lists, project timelines, or agile methodologies. Provide instances where this strategy helped you meet or exceed project expectations.

Research and tie your response to Jellyfish's mission and impact in the engineering management space. Show genuine enthusiasm for contributing to products that help teams work better together, and how that aligns with your professional values.

Be specific about any courses taken, projects completed, or tools used in machine learning or statistical analysis. Mention any relatable experiences that can demonstrate your understanding and interest in this area, even if they were self-taught.

Discuss reliable resources you utilize, such as blogs, webinars, or conferences, to stay informed. Highlight how you apply new knowledge to your work or how these trends could influence your role at Jellyfish.

Share your enthusiasm for data storytelling and how you would present complex information in an engaging manner. You can discuss potential topics you might cover based on trends or findings relevant to Jellyfish's community.