Professional Data Scientist BIG DATA

At AT&T we bring the world together with technology in ways you never imagined. With a range of products and services enhancing how you live, play and work, we’re keeping you connected to the future. We rely on the latest in data science and engineering to curate, analyze and improve our customer experience and operations.

With massive scale comes massive opportunity. The Big Data team at AT&T strives to lead transformation through data-driven decisions that advance the customer experience and businesses around the world. This position is your chance to work with billions of records and gain experience that will make you stand out. With access to one of the coolest, most diverse and largest data sets available in the world, we enable discovery and development of meaningful insights that inspire continuous innovation.

Because of our massive scale of operations, we need help in fully automating many complex processes. We need people who have the capacity to identify problem spaces where Machine Learning has never been applied before and where it can significant impact.
As a data scientist you’ll use your talent for breaking down business challenges into data-driven problems that guide improvements in customer satisfaction and generate millions in savings and potentially revenue. Your solutions could influence everything from fleet optimization and energy efficiency to content analytics and marketing – often before the problem even happens. Add the ongoing skill development and collaboration with some of the brightest minds in the field, and you will be poised to make an impact. You will utilize the latest machine learning and statistical algorithms to create predictive and prescriptive models by detecting and exploiting patterns in massive datasets. You will also create data visualizations and give presentations that will help key stakeholders in their decision making process.
Ready to combine your skills and experience with our innovative technology solutions? We are looking for candidates who love learning new things, like playing with data and want to get things done. We need people that feel comfortable across the entire spectrum of data science, from meeting with business partners and brainstorming on the whiteboard, all the way to implementing and testing their models. You should have an advanced degree in a quantitative field, programming experience with Linux and experience with Machine Learning and/or Statistics. A capacity for translating ambiguous and competing business challenges into concise data-driven problems is very important.


  • An advanced degree in a quantitative field
  • Programming experience with a programming language (preferably Java, Python or R)
  • Knowledge of Unix/Linux systems
  • Self-starter and team player
  • Passionate about constantly learning new skills in a fast-paced environment
  • Ability to communicate with a wide range of audiences, from executives who need the big picture to expert peers that want to learn from your work
  • Capacity to translate complex and open-ended business challenges into concise data-driven problems

Preferred qualifications

  • Experience creating models utilizing Machine Learning and/or Statistics
  • Great intuition, curiosity and skepticism when analyzing data
  • Experience designing and implementing your own algorithms and data structures
  • Exposure to the Hadoop Ecosystem tools (e.g Spark, MapReduce/Tez) or other big data technologies
  • Experience manipulating big and noisy datasets (e.q. SQL, Pig, Hive)

Bonus Points

  • Competitive Programmer or Competitive Data Scientist
  • Committer to Open Source Projects
  • Development of personal projects
  • Knowledge of scalable data visualization techniques
  • Ability to create prototypes quickly
  • Experience manipulating and analyzing large datasets


  • Preferred Masters of Science in Computer Science, Math or Scientific Computing; Data Analytics or Machine Learning nanodegree; or equivalent experience.


  • Typically requires 3-5 years of experience.

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