Job Description:

Job Family Definition:

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.

Management Level Definition:

Contributes to assignments of limited scope by applying technical concepts and theoretical knowledge acquired through specialized training, education, or previous experience. Acts as team member by providing information, analysis and recommendations in support of team efforts. Exercises independent judgment within defined parameters.

Responsibilities:

• Participates in the analysis and validation of data sets/solutions/user experience.
• Aids in the development, enhancement and maintenance of a client's metadata based on analytic objectives.  May load data into the infrastructure and contributes to the creation of the hypothesis matrix.  Prepares a portion of the data for the Exploratory Data Analysis (EDA) / hypotheses.
• Contributes to building models for the overall solution, validates results and performance.  Contributes to the selection of the model that supports the overall solution.
• Supports the research, identification and delivery of data science solutions to problems.
• Supports visualization of the model's insights, user experience and configuration tools for the analytics model.

Education and Experience Required:

• Bachelor´s degree in Statistics, Operations Research, Computer Science or equivalent.

Knowledge and Skills:

• Basic knowledge of data science methodologies.
• Basic understanding of business requirements and data science objectives.
• Basic data mapping, data transfer and data migration skills.  Basic understanding of analytics software (eg. R, SAS, SPSS, Python).
• Basic knowledge of machine learning, data integration, and modeling skills and ETL tools (eg. Informatica, Ab Initio, Talend).
• Basic communication and presentation skills.
• Basic data knowledge of relevant data programming languages.
• Basic knowledge of data visualization techniques.

Health & Wellbeing

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

Personal & Professional Development

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied 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.

Job:

Job Level:

Information about employee benefits offered in the US can be found at https://myhperewards.com/main/new-hire-enrollment.html

Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.

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All legitimate job opportunities will come through official company channels, and candidates are responsible for verifying the credentials of any third party claiming to represent the company. Any reliance on fraudulent communication is at the individual’s own risk, and HPE disclaims legal liability for any resulting damages. If you suspect recruitment fraud, do not share personal information or make any payments and report the incident to your local authorities immediately.