As word spread of the extraordinary return on investment from hiring data scientists, most of the Fortune 500 got in on the hiring. Across industries, spanning the globe, hiring managers and recruiters are buzzing about the high demand for this new breed of big data professionals. Nearly every major tech player on the Internet – Google, Facebook, Amazon, EBay, PayPal, Twitter, et al – is keen on harnessing user data to shape their business plans. They now know the best way to do so is by hiring data scientists.
The following job candidate profiles are culled from recent data scientist postings by some of the biggest tech companies. Each of these jobs requires a master's or PhD and four years of relevant work experience in statistics, computer science, mathematics, or other related fields, as well as expert knowledge of data analysis tools and computer programming language. For more information on a recommended master's degree in data science, read about our partner UC Berkeley's master’s program.
The ubiquitous search engine digs deep for data.
“As a decision support engineering analyst, you will help evaluate and improve Google’s ads. You will collaborate with a multi-disciplinary team of engineers and analysts on a wide range of problems. This position will bring analytical rigor and statistical methods to the challenges of measuring ads quality, looking into problems such as how to optimize both our ads quality and our revenue and how to build models of end-user behavior.”
The social network relies on data science.
“Individuals in this role are expected to be comfortable working as a software engineer and a quantitative researcher. The ideal candidate will have a keen interest in the study of an online social network, and a passion for identifying and answering questions that help us build the best products.”
The discovery engine uses big data to recommend web content to users.
“You will have access to data on over 15 billion stumble/rating/review records, as well as preference and markup data on over 50 million websites, and 15 million users. You will write data mining algorithms and/or work with data mining tools in order to discover interesting patterns and track changes in the data. You will present your findings to the research team and eventually the whole company.”
The online deal finder relies on data scientists to expand its network.
“Are you passionate about large-scale data analysis and modeling? Do you wish you had the opportunity to translate your ideas to practical solutions for some of the most interesting and challenging problems in the Internet industry? And most importantly, are you excited to be part of a fun, fast-paced and growing team with lofty ambitions?”
The Internet’s biggest pay site uses data science to raise its online profile.
“This position is part of a Big Data Platform team at PayPal – focused on Risk Management. This is a unique opportunity to be part of a core team of machine learning engineers and scientists; an opportunity to build solutions for managing and mining big data. We work very closely with the statisticians and analysts to apply advance analytics techniques to solve fraud detection business problems.”
The ADP automobile spin-off uses data analytics to connect consumers with auto dealers.
“Do you enjoy finding opportunities to exploit by digging through large data sets? Are you a hacker who can throw together a system that leverages and automates your findings? Does the idea of being one step ahead of the competition excite you?”
The real estate portal hires data experts to help them boost web traffic and expand their network.
“As a part of Trulia’s new data science lab, you’ll have the opportunity to work with massive datasets – think trillions of user actions and millions of homes. You’ll get to work on (and help build) a team that loves AI technologies, and can’t get enough of data visualizations. You’ll get to propose projects, and see them through the whole lifecycle.”
The innovators of the wireless activity tracker are in the market for big data experts.
“We are building a world-class research team of hacker-scientist types to dream up, prototype, and deliver shipping products. A successful candidate will have deep experience in applying machine learning and statistics toward understanding structured and unstructured data. Research responsibilities will include exploratory data analysis, data visualization, and developing prototypes and metrics to drive product and business decisions.”