Data Scientist

JOB DESCRIPTION

Hewlett Packard Enterprise creates new possibilities for technology to have a meaningful impact on people, businesses, governments and society. HPE brings together a portfolio that spans software, services and IT infrastructure to serve more than 1 billion customers in over 170 countries on six continents. HPE invents, engineers, and delivers technology solutions that drive business value, create social value, and improve the lives of our clients.

Learning does not only happen through training. Relationships are among the most powerful ways for people to learn and grow, and this is part of our HPE culture. In addition to working alongside talented colleagues, you will have many opportunities to learn through coaching and stretch assignment opportunities. You’ll be guided by feedback and support to accelerate your learning and maximize your knowledge. We also have a “reverse mentoring” program which allows us to share our knowledge and strengths across our multi-generation workforce.

HPE Software has a wide variety of Software Solutions and Services that allow customers to: deliver amazing applications, re-invent IT operations, optimize and monetize customer engagement, identify and neutralize security threats, and protect and govern data assets. HPE Software is a fast growing business unit which supports its customers on planning, conceptual design and implementation of software solutions. Big Data has changed the software landscape and HPE is leading the way

Designs, develops, troubleshoots and debugs enterprise class software on multiple platforms.

You will discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems to enable our customers to get insight into the multi-domain data collected by our suite of products

Responsibilities

  • Selecting features, building and optimizing classifiers using machine learning techniques
  • Data mining using state-of-the-art methods
  • Applying advance/deep analytics to build complex network models for prediction
  • Processing, cleansing, and verifying the integrity of data used for analysis
  • Enabling our customers doing ad-hoc analysis and presenting results in a clear manner
  • Creating automated anomaly detection systems and constant tracking of its performance

Hewlett Packard Enterprise Values:

Partnership first: We believe in the power of collaboration – building long term relationships with our customers, our partners and each other

Bias for action: We never sit still – we take advantage of every opportunity

Innovators at heart: We are driven to innovate – creating both practical and breakthrough advancements

What do we offer?

Extensive social benefits, flexible working hours, a competitive salary and shared values, make Hewlett Packard Enterprise one of the world´s most attractive employers. At HPE our goal is to provide equal opportunities, work-life balance, and constantly evolving career opportunities.

If you are looking for challenges in a pleasant and international work environment, then we definitely want to hear from you. Apply now below, or directly via our Careers Portal at www.hpe.com/careers

You can also find us on:

https://www.facebook.com/HPECareers

https://twitter.com/HPE_Careers

Education and Experience

  • B.E/B.Tech or Master’s degree in Statistics , Computer Science , Information Systems
  • 6-10 years with minimum 4 years of relevant experience

Skills

  • Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
  • Experience with common data science toolkits, such as R, NumPy etc Excellence in at least one of these is highly desirable
  • Great communication skills
  • Proficiency in using query languages such as SQL
  • Experience open source big data platforms like Vertica, Elastic search
  • Good applied statistics skills, such as distributions, statistical testing, regression, etc.
  • Good scripting and programming skills in Java, Python, Go
  • Data-oriented personality

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