FAQs
How can I apply for a job?”
Please go to https://www.bu.edu/spark/students/work/, where you will find the “Spark! Employment Opportunities” tab. Please reach out to buspark@bu.edu if you have any further questions or concerns.
What does the tech hiring process involve?
- Applications reviewed
- Invite to Technical Interview
- SE: technical assessment + meeting
- DS/ML: 30 minute interview
- Decision making
- Send out offer
Internship Program Prerequisites
UX Design: Minimum prerequisite DS280 or DS488 or XC475 or a portfolio of UX design work completed independently e.g. through projects worked on via a club (Forge) or internship.
Project Manager: Usually preference is given to students who have worked on an X-Lab project previously in one of our practicum courses, but generally someone who is proactive, has strong project management and communication skills with basic understanding of data science, or software engineering projects. For students seeking project or product management experience, we encourage them to take Introduction to Product Management for Data Science (CDS DS 719), a 2-credit course where students will learn about scoping and managing a technical feature from concept to launch, identifying and tracking success metrics, and ensuring customer satisfaction and smooth team collaboration.
Spark! Ambassador: Passion for technology, but no technical skills required, proactive, organized, ability to work independently takes initiative, cares about building community, committed to inclusive practices, ideas oriented, strong communication skills. Ambassador tracks include:
- Community: Organize social events and activities aimed at connecting students and promoting wellness and community.
- Learning: Recruit speakers and set topics for Spark! TechTalks, organize MicroChallenges, and support with career development initiatives.
- Hackathon: Organize hackathons throughout the school year and support students at all levels of computing and data science.
- Ignite: Support tech-focused clubs through promotion, training, recruitment, and more.
- JEDI: Support Spark!’s efforts to advance justice, diversity, equity, and inclusion, including the DEI in Tech Collective, DEI training, and the DEI in Tech course.
I am a freshman or a sophomore, can I get hired for an internship?
We have select opportunities for sophomores in our Summer internship program. We highly suggest freshmen and sophomores to attend our TechTalks and to participate in our MicroChallenges. TechTalks and MicroChallenges help students to build skills in different areas including software engineering, data science, and machine learning. Typically, internship openings during the semester are for project support roles (Technical Project Manager). Usually preference is given to juniors/seniors or students who have worked on an X-Lab project previously in one of our practicum courses.
What’s the difference between a technical intern and technical project manager (TPM)?
Technical Interns work on the data science, machine learning, or software engineering components of real-world technical projects for an external partner.
Technical Project Managers (TPMs) oversee the technical components of a portfolio of projects, proactively ensuring client satisfaction with a student team’s technical work. TPMs are responsible for providing teams with feedback on their technical work, code reviews, answering technical questions from their teams, and escalating to Spark! Technical Leadership as requested.
What should I expect from the technical interview?
Spark! technical interviews do not require applicants to solve leetcode problems or code live. The goal of the technical interview is to help Spark! staff get a better understanding of a candidate’s technical competency. For software engineering, this is through a technical assessment and interview. For data science and machine learning, this is through questions on data science and machine learning concepts.
How many technical interns does Spark! hire each semester?
The number of technical interns Spark! hires each semester depends on project needs, which varies semester to semester. For TPMs, we typically need 12 Data Science TPMs, 2 Machine Learning TPMs, and 2 Software Engineering TPMs. These numbers are estimates and may fluctuate depending on the class sizes and the number of projects we have.