Data Scientist

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!

Printing is a large contributor to the success of HP. The company's consumer and commercial printing solutions lead the market around the globe, and the Big Data Business Transformation Center of Excellence contributes critically to the business strategy, planning, and operations of HP's printing business.

  • As a Data Scientist leader on this team, you will directly shape the future of advanced analytics at HP by developing cutting edge analytic capabilities for use in the business. You will work on highly relevant opportunities, collaborating with a team of data scientists and business analysts to create, enhance and execute high-impact advanced analytic solutions across HP's global printing business. You will employ advanced analytic techniques in exploration of actionable insights and development of these new capabilities.
  • Qualified candidates will have expertise in computer science, statistical modeling, leading-edge quantitative techniques, data mining, and a strong business acumen.
  • Propose, investigate, develop and refine new analytic capabilities for deployment in the business. Build algorithms, tools and custom solutions for use by business analysts and forecasters.
  • Manipulate and analyze large data sets using industry standard tools and techniques. Extract quantitative and qualitative findings from large data sets.
  • Architect, build and prototype new data models and pipelines that deliver intuitive analytics to our customers.
  • Maintain an understanding of division strategic goals, business challenges and customer needs to support identification and development of novel analytic approaches that solve key business problems.
  • Prepare and present findings of investigations to management.
  • Train partner teams on use of new analytic tools and methods.

Education and Experience Required:

  • Typically 5-7 years total experience. Often several years post advanced degree experience leading data science and business analysis projects.
  • Advanced university degree (e.g., MS, PhD) or demonstrable equivalent in quantitative field preferred (Computer Science, Statistics, Economics, Advanced Analytics, Operations Research, Applied Mathematics, Decision Sciences, etc.).
  • Knowledge and Skills:
  • Expert experience with dimensional modeling, Big Data solutions and ETL development.
  • Solid experience in investigative analysis and technical debugging, Ability to troubleshoot and identify root cause.
  • Knowledge of applied statistics, machine learning, data mining, and predictive analytics.
  • Expert-level experience in data science and visualization toolkits (R, SAS, Python, Tableau). Fluency in SQL.
  • Proven ability to sift through data, identify critical information, develop hypotheses, identify appropriate data science techniques and perform rigorous analyses to deliver new insights and solve business problems.
  • Experience applying critical thinking to analyze processes and data anomalies to diagnose data issues.
  • Strong oral and written communication skills, including the ability to communicate findings to stakeholders and document project steps in detail.
  • Ability to work individually, as well as partner with small teams of Data Scientists during all stages of projects, including planning and execution.
  • Ability to independently manage complex project objectives and complete multiple simultaneous project tasks with little supervision.
  • Familiarity working with large-scale datasets and big data techniques.
  • Experience with AWS ecosystem a plus.

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