Lead Machine Learning and Data Sciences

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Employer: HP Inc.
  • IT Software
  • Job type: full-time
    Job level: 1 - 5 years of experience
  • Updated at: 18.11.2019
    Short company description

    At HP, we believe in the power of ideas. We use ideas to put technology to work for everyone. And we believe that ideas thrive best in a culture of teamwork. That is why everyone - at every level in every function, is encouraged to have original ideas, to express them and to share them. We trust anything can be achieved if you really believe in it, and we will invest in your ideas to change lives and the way people work. This vision is what sets us apart as a company. At HP we work across borders, and without limits. Global virtual teams share resources and pool their big ideas to solve business issues and meet personal goals. Everyone is valued for the unique skills, experiences and perspective they bring. That’s how we work at HP. And this is how ideas and people grow.

    HP is a proven leader in personal systems and printing, delivering innovations that empower people to create, interact, and inspire like never before. We leverage our strong financial position to extend our leadership in traditional markets and invest in exciting new technologies.
    HP has an impressive portfolio and strong innovation pipeline across areas such as:
    • blended reality technology - our unique Sprout by HP will change the way people do things
    • 3D printing
    • multi-function printing
    • Ink in the office
    • tablets, phablets, notebooks
    • mobile workstations

    We’re looking for visionaries who are ready to make an impact on the way the world works. At HP, the future’s yours to create!


    Bachelor's, Master's or PHD degree in Mathematics, Economics, Physics, Computer Science, Data Sciences, Statistics, Engineering or equivalent.
    Typically 4-6 years experience including graduate or postgraduate research.
    Some background in developing predictive modeling algorithms using PythonR, along with other tools in the Apache Big Data stack.
    Good understanding of statistical and machine learning algorithms such as Regression, Classification, Clustering or Neural Networks.
    Candidates with prior industry experience preferred.
    Using statistics, mathematics, algorithms and programming languages.
    Understanding of how to manage disparate unstructured and structured data in a distributed environment.
    Fluent in structured and unstructured data and modern data transformation methodologies.
    Ability to create models to pull valuable insights from data.
    Create stories and visualizations to describe and communicate data insights.
    Ability to use creativity to spot trends and tease out patterns in large datasets.
    Strong analytical and problem-solving skills.
    Excellent written and verbal communication skills; mastery in English and local language.
    Ability to effectively communicate data insights to project team and leadership and negotiate options.
    Proficiency with SQL and hands-on skills in an analytics platforms and software such as R, Python, Scala or Java.
    Ability to work with and fetch data from big data file storage systems like hdfs, aws stacks, api pulls.
    Ability to bring in new ML and AI tools and capabilities as well as big data framework tools to help build, automate and scale the models and algorithms.
    Ability to build end-to-end solutions for showcasing value to stakeholders.


    Mines data using modern tools and programming languages.
    Defines and implements models to uncover patterns and predictions creating business value and innovation.
    Works with the business to understand the business domain perspective.
    Effectively tells stories with the data using visualization toolsmethods to demonstrate insight impact and business value.
    Assures accuracy, integrity, and compliance of cleansed data.
    Maintains proficiency within the data science domain by keeping up with technology and trend shifts.
    Leads a project team of data science professionals
    Collaborates and communicates with project team regarding project progress and issue resolution.
    Represents the data science team for all phases of larger and more-complex development projects.
    Provides guidance, training and mentoring to less experienced staff members.