Twitch is a live video streaming platform that allows users to watch and broadcast live-streamed or pre-recorded videos of the broadcaster’s video game gameplay. The platform is owned and operated by Twitch Interactive, a subsidiary of Amazon. Founded in 2011 as an offspring of the “stream anything platform”, Justin.tv, its prime focus is on streaming live video games, including broadcasting Twitch’s own hosted eSports competitions. Besides these functions, Twitch also broadcasts music and creative content, which can be viewed live on the site or from “Video on Demand”.
As of Q4 of 2019, Twitch has over 3.6 million average monthly broadcasters, just shy of figures above 3.8 million from March 2020. With over 56 thousand concurrent Twitch broadcasters and 1.44 million concurrent viewers on average, Twitch’s web APIs handle over 50 thousand requests a second, which translates to over 2.3 billion hours watched in 2019.
With the amount of data generated from different daily streams, Twitch’s data science team performs a wide range of analysis to help shape product decisions. This feat is achieved through enhanced data pipelines “that collects data, cleans data, and loads over a billion events per day into their data warehouse.”
Twitch has a “science team”, consisting of titles and roles related to data science. It is supported by three pillars, namely “data science research, user experience research, and data governance.” Data science sits right in the middle of these three science organizations and collaborates with the other teams on many occasions.
Data scientists’ roles at Twitch are greatly influenced by the teams they are working with, and, as such, the roles and functions may range from product-focused analytics to machine learning and deep learning algorithms. Currently, there are two main types of data scientists: the “product strategy-oriented data scientists”, who provide business-impact insights from data analysis, and the “data product data scientists”, who build specific algorithms and techniques yield new products informed by data.
Twitch only hires qualified data scientists with a minimum of 3 years (5 years plus for senior data scientist roles) industry experience in data science-related projects.
Note: applications are processed and evaluated based on specific industry experience related to the job roles on the teams.
Other relevant qualifications include:
Although Twitch has a dedicated “Science Team” consisting of data scientists, data analysts, and data engineers, data scientists are often embedded within other teams and sometimes collaborate with other departments. As a large company with data scientists working in over 20 teams, on the individual level, roles at Twitch are inherently tied to specific teams.
Based on the team’s needs, data scientist roles at Twitch may include:
Twitch’s initial data scientist screen interview is a 30 to 60-minute phone chat with a hiring manager, discussing the team, Twitch as a community, your ideas on data, your technical background, and how your past relevant projects and experiences align with the job roles on the team.
Twitch’s data scientist technical screen is very similar to most tech companies. This interview involves a one-hour live screening on a coderpad with a data scientist, and the questions asked are usually SQL-based. There is also an element of behavioral and background experience in this interview.
The onsite interview is the last stage in Twitch’s data scientist interview process. This process comprises 6 one-on-one interviews (or conferences) split around behavioral, experimental, SQL, and coding questions with a product manager, data scientists, technical product manager, and analyst.
Each interview is approximately 45 minutes long, and the questions on these interviews tend toward experimentation, A/B testing, business intelligence, and heavy analytics. There are also product-focused and behavioral rounds, with questions around business analytics experience, past working experience, and your knowledge of Twitch’s culture. Take a look at our guide to data science case studies for practice.
Twitch’s Data Scientist interview is a combination of data science concepts standardized to assess an applicant’s ability to apply statistical and analytics concepts to understanding and predicting user behavior and answering business questions based on the analysis.
It helps to brush up on your knowledge of:
It also helps to know the metrics used at Twitch, especially those related to products and features.
Twitch offers an ecosystem that allows employees to thrive and be the best version of themselves by encouraging them to get their hands dirty and find something they love. A lot of emphasis is placed on building high-performing teams through mentorship programs, and in fact, the ability and desire to mentor is something Twitch looks for in applicants.
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