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How Gusto scales their data science capabilities with Deepnote

To support Gusto's growing customer base, the company is scaling their data science capabilities across 2 different roles: Models & Algorithms and Product Analytics. With the shift to remote work, Gusto was looking for a tool that would streamline and support their data science interviews. Legacy tools were not reliable for real-time collaboration between interviewers and applicants. After evaluating Deepnote against other computational platforms, the Gusto team selected Deepnote as their tool of choice.

Use cases

Data science interviews

Data stack

Python, R, PostgreSQL, GitHub

Gusto about 1
Gusto about 2
01

Notebook setup within seconds

Deepnote helps the data science team at Gusto streamline the interview workflow. The team has created a set of template notebooks that can be duplicated in seconds. In preparation of an interview, the hiring team simplyduplicates the template and shares a URL link with the applicant. The notebooks connect to PostgreSQL databases directly, so the data is instantly ready. The interviews leverage different kernels, a common use case is running SQL queries and Python code in one project.

02

Real-time collaboration

During the interview, the interviewers and the applicant collaborate in the same notebook in real time. Deepnote allows both to see where the other person is in the notebook, view the changes as they are being made and execute code collaboratively, since they are sharing the same environment and kernel. This way, the interviewers can ask follow-up questions and lead the interview in a conversational way.

03

Easy access management

Using the granular Deepnote access permissions, interviewers can determine the right level of access rights for all stakeholders involved in the interview process - from admin rights for the data science team members, view rights for recruiters, all the way to temporary edit rights for job applicants. This way, the applicant can explore connected data, run and modify code, but she has limited access to the environment and the source data is secure. To protect the templates from being shared externally, interviewers remove access for applicants immediately after the job interview ends in one click.

Great window into the ways candidates approach the interview problem

We'd had a lot of technical issues when trying to pair up on other notebooks during remote interviews. Deepnote was incredibly easy to set up and allows us to start new notebooks in seconds. Working together with Deepnote gives us a great window into the ways candidates approach the interview problem.

Becca CarterData Scientist & Product Analytics lead at Gusto
Becca Carter's avatar

Outcome

Using Deepnote, Gusto is able to conduct interviews at scale and involve the whole team in a streamlined process that allows for sophisticated collaboration. Most importantly, interviews take place in an environment that closely mimics a normal collaborative work environment helping interviewees get a realistic feel for the role itself.

We look forward to Gusto's successes and encourage anyone interested in joining the Data science team to view the current job openings.

Outcome for Gusto

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