Data Scientist

This role has been designed as ‘Hybrid’ with an expectation that you will work on average 2-3 days per week from an HPE office.

Who We Are:

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know diverse backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.

Job Description:

Designs, develops and applies programs, methodologies and systems based on advanced analytic models (e.g. advanced statistics, operations research, computer science, process) to transform structured and unstructured data into meaningful and actionable information insights that drive decision making.

Uses visualization techniques to translate analytic insights into understandable business stories (eg. descriptive, inferential and predictive insights).

Embeds analytics into client’s business processes and applications. Combines business acumen and scientific methods to solve business problems.

Contributions include applying developed subject matter expertise to solve common and sometimes complex technical problems and recommending alternatives where necessary. Might act as project lead and provide assistance to lower-level professionals. Exercises independent judgment and consults with others to determine best method for accomplishing work and achieving objectives.

Responsibilities:

• Formulates and defines analytics solution objectives and technical requirements based on user needs, an understanding of business processes, industry requirements, and advanced analytic models (statistical, operations research, computing, process).
• Conceptualizes, builds, develops and enhances a client's analytic model. Selects the relevant analytic modeling methodology for the use case, available structured and unstructured data, cost and timing constraints to solve the business issue and deliver clear business focused insights.
• Embeds analytic models in an enhanced business process of operational system by collaborating with Application Developers. Responsible for measuring business performance based on the model.
• As a fully functioning analytics team member, applies best practices to analytics solutions and contributes to the development of improved best practices. Leads the model enhancements.
• Summarizes complex ideas by developing visual models to display insights to simplify user experience.
• Communicate the analytics solution to the appropriate stakeholders.

Education and Experience Required:

• PhD degree in Statistics, Operations Research, Computer Science or equivalent preferred. Or Master´s Degree in these areas and at least 2-3 years of relevant experience.
• Bach. Degree in related field at least 3-5yrs of relevant experience.

Knowledge and Skills:

• Advanced knowledge of advanced data science methodologies including but not limited to classical regression, neural nets, CHAID, CART, association rules, sequence analysis, cluster analysis, and text mining.
• Ability to translate business requirements into mathematical models and data science objectives to achieve measurable business outcomes.
• Advanced understanding of analytics software (eg. R, SAS, SPSS, Python). Advanced understanding of analytics deployment architectures.
• Advanced machine learning, data integration, and mathematical modeling skills and ETL tools (eg. Informatica, Ab Initio, Talend).
• Advanced communication and presentation skills.
• Strong interpersonal skills and effectiveness in working across geographical boundaries.
• Working knowledge of programming languages such as Python, SQL, R, SAS, Java, Unix Shell scripting. Working knowledge of Hadoop framework desired.
• Advanced knowledge of data visualization techniques and software tools (eg. Spotfire, SAS, R, Qlikview, Tableau, HTML5, D3).