Data Science Internship- Summer 2025

As a Data Science Intern at SPAN, your core responsibilities will revolve around collecting and analyzing data sets, prototyping new features, and collaborating with engineers to ensure cohesive product development. You'll also engage with non-technical stakeholders, giving you a holistic view of the product lifecycle.

To qualify for the Data Science Internship at SPAN, you should be pursuing a degree in fields like computer science, applied mathematics, or statistics. A strong understanding of machine learning techniques and proficiency in Python and SQL are key requirements. Familiarity with electrical engineering and cloud computing platforms like AWS would be a bonus!

The Data Science Internship at SPAN is a 12-week program, starting in May or June of 2024. This timeframe allows you to immerse yourself fully in hands-on projects while contributing to SPAN’s mission towards a cleaner environment.

At SPAN, you will have ample opportunity for learning and growth during your Data Science Internship. You'll engage in diverse projects, collaborate with seasoned professionals, and receive guidance that aligns with your academic background and career aspirations, fostering your development in the tech industry.

The company culture at SPAN is vibrant and inclusive, emphasizing teamwork and open communication. As a Data Science Intern, you'll experience a supportive environment that encourages collaboration and innovation, making it an ideal place to hone your skills and contribute to meaningful projects.

In answering this question, highlight specific instances where you handled raw data and transformed it into a usable format. Discuss the tools and techniques you used to clean datasets, and be prepared to talk about any insights or findings that resulted from your analysis.

When discussing a machine learning project, describe the problem you were trying to solve, the data you used, and the algorithms you applied. Emphasize your role, how you approached the project, and any challenges you overcame, showcasing your problem-solving skills.

Share your strategy for prioritizing tasks based on deadlines and project importance. Describe how you communicate with your team to ensure alignment, and give an example of a time when effective prioritization helped you meet a critical deadline.

Mention the programming languages you are proficient in, emphasizing Python and SQL for their relevancy in data analysis. You can also mention any projects where you applied these languages and how they facilitated your work.

To effectively communicate technical concepts, focus on simplifying the language you use. Provide analogies and visual aids where possible. Give an example of a time when you successfully conveyed a complex topic to a non-technical audience.

In answering this question, illustrate your teamwork skills by detailing your role in the project, the team's objectives, and how you contributed. Discuss any challenges faced and how collaborative efforts led to successful outcomes.

Mention specific tools you've utilized, such as Python libraries (like pandas and NumPy), SQL databases, or visualization tools (like Tableau or Matplotlib). Talk about how these tools aided your analysis and any key results you achieved using them.

Explain your methods for ensuring data accuracy, such as implementing verification checks and using validation datasets. Discuss a scenario where your attention to detail led to discovering an error and rectifying it.

Share genuine reasons for your enthusiasm about SPAN’s commitment to electrification and decarbonization. Connect your personal values or career ambitions to SPAN's mission, demonstrating a shared commitment to creating a sustainable future.

Express your career goals and what you hope to learn during the internship, such as gaining practical experience in data science, honing technical skills, and contributing to real-world projects. Show enthusiasm for the opportunity to work with SPAN's innovative team.