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Sr Engineer Advanced Analytics Data Scientist - Seagate

Seagate Technology


Location:
Minneapolis-St. Paul-Bloomington, Minnesota
Date:
03/30/2017
Categories:
  • Data Analytics
  • Data Engineer
  • Data Scientist
  • Statistician
Seagate Technology
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Job Details

The Advanced Analytics team in Seagate’s Operations and R&D organization is seeking a talented Data Scientist to help our internal customers turn data into information to develop and deliver industry leading storage solutions.

This position will report to the Managing Principal Engineer of Advanced Analytics Development.

This outstanding individual will understand the meaning of “Science” in Data Science. The problems are not straightforward or easily solvable and the discovery may lead to discoveries by others. This is revolutionary not evolutionary work.

A key function of this role is to facilitate the advancements of modern analytical techniques across Seagate’s Operations and R&D organization. Will be an evangelist and an assessor promoting new ways of diving into complex issues while assessing current practices and identifying areas where training or knowledge would help.

 

Responsibilities

  • Work with business unit subject matter experts and the Principal Data Scientist to identify, prioritize and answer important business questions through the development of innovative algorithms and visualizations using modern analytical techniques in Data Mining, Machine Learning and Statistics
  • Leverage and/or develop innovative data mining and machine learning methods to solve novel and diverse business problems
  • Quantify the effectiveness and value of innovations with subject matter experts
  • Collaborate closely with our Data Engineering team who will provide access to diverse data streams from across the company and enable deployment of innovations throughout the enterprise
  • Demonstrate proofs of concept and develop prototype systems that can be further developed and deployed on enterprise platforms by the Data Engineering and other teams within Seagate
  • Document discoveries and share knowledge with technical stakeholders around the company
  • Translate insights about complex issues into simple explanations and visualizations to aid understanding by a wide range of audiences
  • Explore ways to transform structured and unstructured data from multiple sources to facilitate analyses
  • Actively participate in a peer review process for new and existing mining and modeling techniques, giving and receiving constructive feedback to constantly improve the application
  • Collaborate with IT and other organizations that are pursuing Data Systems and Advanced Analytics to identify and integrate "best in class" systems and methods

Requirements

Requirements 

  • Master’s degree with 3+ years’ related experience, or PhD with 0-2 years' related experience.
  • Engineering or science discipline such as Computer Science, Physics, Chemistry, Statistics, Mathematics, Electrical Engineering, Mechanical Engineering, etc.
  • Advanced experience with innovative algorithms and visualizations using modern analytical techniques in Data Mining, Machine Learning and Statistics
  • Software development experience with scripting languages and software platforms related to Advanced Statistics, Data Mining, Machine Learning and Visualization (ex. SQL, SAS, JMP, R, python, Tableau)
  • Creative, open minded, and relentless pursuit of breakthrough solutions while also taking pride to see colleague's work cited
  • Demonstrated on-going learning to keep up with technological advances.
  • Ability to develop high levels of credibility and forge solid, positive, professional team relationships with peers and upper management
  • Strong oral and written communication skills, as well as the ability to interface internally and externally with all levels of management
  • Collaborative attitude and a global mindset with an ability to work well with native and non-native English speakers
  • Able to travel ~15-20%, including international

     

Preferred Qualifications

  • Domain knowledge of a business area such as process or industrial engineering, development, manufacturing or supply chain
  • Thesis or research experience in topics related to predictive analytics such as data mining, pattern recognition, image processing, data-driven prognostics, fault diagnostics, artificial intelligence and machine learning