Company Guides

Twitch’s data science team performs a wide range of analysis through enhanced data pipelines “that collects data, cleans data, and loads over a billion events per day into their data warehouse.”

Data scientists at Pinterest leverage the most advanced analytics tools and machine learning models to make sense of data for guiding business decisions.

Business analysts at Google analyze data to develop different insights to drive business decisions for products.

What company size is best for you? The answer lies in realizing the major differences between the types of companies.

Lyft's data science department is tasked with leveraging the most advanced analytics, machine learning, and big data tools in providing business models and insights

Data analysts at Amazon help bridge the gap between data and the decision-making process.

At Deloitte, data scientists largely contribute to consulting roles on other teams, working to provide basis and information for decisions.

Business intelligence engineers translate the large data warehouse at Amazon into meaningful insights and improvements

The Amazon business analyst interview questions, process, and hiring tips.

The Snapchat data science interview questions will consist of a wide-breadth of problems that test the full-stack knowledge of data science.

Google asks about 5+ different topics in data science spanning machine learning, statistics & probability, product & business, and coding.

Data scientists at Google work across a wide facet of teams, products, and features, from enhancing advertising efficacy to network infrastructure optimization.

The onsite consists of five rounds of interviews. These interviews are composed of a mixture of behavioral, software engineering, and machine learning questions.

How would you create a process to identify fake news postings on Facebook?

Data scientists at NVIDIA leverage the most advanced data science technology in their products that ultimately get used in professional visualization, data centers, artificial intelligence, virtual reality, and self-driving cars.

Walmart has a data science and analytics departments with many roles like data scientist, data analyst, big data engineer, and tech architect

Data analysts at Facebook work on many different teams and are extremely cross-functional

Square generates billions of monthly transactional data which forms the basis of analysis at the company

From teams such as Small Business to Machine Learning Futures, data scientist teams at Intuit analyze data and deploy ML and AI models to solving business-related problems.

Data scientists help develop and improve the models that power DoorDash’s three-tier marketplace of consumers, merchants, and dashers.

Netflix has over the years been leveraging data science for its content recommendation engine, to decide which movies and tv shows to produce and to improve user experience.

From its researched-based artificial intelligence development team at Siri to cloud-base architecture development team at iCloud, Apple has slowly but steadily been building data science teams.

The data science role generally covers basic business analytics, modeling, machine learning, and deep learning implementation.

Aside from being one of the biggest tech companies, Twitter also has one of the world’s largest real-time datasets.

Data scientists generally oversee most of the products. To succeed at LinkedIn, it’s important to work on big projects and push them through.