We’re excited to announce a partnership with Data Society to give students new opportunities to showcase their portfolio of work as they develop their data science skills. Similar to how developers use GitHub and designers use Dribbble to show off their work, data.world profiles are an ideal place for a data scientist to represent their professional work.
This partnership enables students to find and access datasets from data.world that are relevant to the specific technique (e.g., Clustering and Finding Patterns) that a student is studying within the Data Society platform. Unlike the datasets used in typical classroom exercises, these datasets provide students with opportunities to find insights around real-world scenarios. Projects that are completed using these datasets are impactful both for skill development and for showcasing a student’s capabilities. The screenshot below shows curated datasets that students would find alongside the Regression course on Data Society.
Students are encouraged to use datasets from data.world to hone their skills and showcase their work. data.world makes exploratory analysis, linking, and querying data quick and allows users to interact with data using our R SDK, Python SDK, or APIs. As a student works on a project, she can show her work by including transformed data, queries, scripts, analysis, visualizations, and written narrative. This is a great way to position herself well for the hyper-competitive data job market. Check out this project that analyzes the impact of income on cancer clinical trial access to see a great example of how you can show off your data analysis.
I have interviewed hundreds of candidates and hired dozens of employees for roles across functional areas at data.world, at my own start-ups, and on Wall Street. The first thing that I and other hiring managers look for when screening candidates is expertise. But if I’m interviewing students or people changing careers, they can stand out by demonstrating their interest in the area and for the role that they are pursuing. Demonstrable interest can range from completing a single course, to taking a leadership role in a student club or leading a Meetup group, to pursuing an academic major or enrolling in a training program, to taking on a tangible project. Without professional experience in an area, showcasing a portfolio of projects is far and away the most impactful step a candidate can take to show that she is prepared, serious and capable.
Interviews where a candidate has completed an interesting independent project often are the most engaging for the interviewer and provide the candidate the best opportunity to distinguish herself. Not only does the candidate demonstrate an understanding of the data science process — moving from question to data discovery to data preparation to analysis to presentation of implications — but also provide strong signals of having significant initiative and creativity.
Beginning this week, you’re invited to participate in a monthly dataset challenge to create interesting visualizations and compelling analyses. data.world will recognize your work and share the most interesting analyses and visualizations with its data science community (plus, there may be some prizes in the mix). You’ll find the first challenge announced soon in the Data Society newsletter!
I’d love to see your work on data.world so tag @len in a discussion on your dataset on data.world or leave me a comment below.