The Opportunity:Shutterstock is a growing, fast-paced, entrepreneurial company operating within a disruptive industry for over 15 years. Well-positioned as the leader in the digital content space, Shutterstock has the largest crowd-sourced digital content library in the world, including leading collections of images, vectors, music, and video. We manage a library of creative building blocks for an expanding global customer base.
Shutterstock adds hundreds of thousands of images, video and audio content each week, and currently has more than 400 million images and more than 20 million video clips available.
Headquartered in New York City, Shutterstock has offices around the world and customers in more than 150 countries. The company also owns: Bigstock, a value-oriented stock media agency; Shutterstock Custom, a custom content creation platform; Offset, a high-end image collection; PremiumBeat, a curated royalty-free music library; and Shutterstock Editorial, a premier source of editorial images for the world's media.
Our Creative platform supports photographers, advertisers, film & television studios, marketers and publishers to produce and consume amazing content, while our Editorial business is a world leader in the production and distribution of real-time celebrity, sports, fashion and news photography, as well as covering events such as the Academy Awards, London Fashion Week and the Met Gala.
Shutterstock is looking for Data Engineering interns to join our product teams, working on the future of our creative and predictive performance platforms.
You will be working with highly motivated and extremely talented data engineers on large datasets, analytics and visualization tools and, finally, deep learning and machine learning. Our core belief is that the customers are our number one priority so we work hard to deliver value back to them with everything we do. We believe strongly in team ownership of systems, which includes defining the vision of the services to prioritization of projects.
- Participate in all aspects of the services under the team’s ownership, which includes design, implementation, automated testing, deployment, and uptime of the services.
- Participate in the code review process, paired programming.
- Work alongside Senior Data Scientists, Product Manager and Designers on the development of the services under the team's ownership.
- Building the technology the right way: for us, this means simple, well-tested systems that gradually grow over time, and that provide plenty of insight into production performance.
Ideal candidate would have one or more of the following:
- Experience in Data Science fundamentals and machine learning libraries
- Applied statistics skills, such as distributions, statistical testing, regression, etc.
- Understanding of common Natural Language Processing and Data Science libraries
- Passionate about what you do and care deeply about the things you build.
- Able to clearly communicate to team members.
- Has a good understanding of continuous delivery.
- Notebook experience [Jupyter, Zeppelin, Databricks, etc.] to perform data analysis and algorithm development using Python
- Natural language processing experience, ranking and classification