Hewlett Packard Enterprise is looking to transform structured and unstructured data into meaningful and actionable information insights that drive decision making by designing, developing and applying programs, methodologies and systems based on advanced analytic models.
Requirements
- 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 data knowledge of relevant data programming languages.
- Basic knowledge of data visualization techniques.
Responsibilities
- 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.
- 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.
- Contributes to building models for the overall solution, validates results and performance.
Other
- This role has been designed as ‘Hybrid’ with an expectation that you will work on average 2 days per week from an HPE office.
- Bachelor´s degree in Data Science, Statistics, Operations Research, Computer Science or equivalent.
- Typically 0-2 years experience.
- Basic communication and presentation skills.
- Contributes to assignments of limited scope by applying technical concepts and theoretical knowledge acquired through specialized training, education, or previous experience.
