Compute Quality Data Scientist

This role has been designated 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.

What you will do:

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:

Applies intermediate level of subject matter knowledge to solve a variety of common business issues. Works on problems of moderately complex scope. Acts as an informed team member providing analysis of information and limited project direction input. Exercises independent judgment within defined practices and procedures to determine appropriate action. Follows established guidelines and interprets policies. Evaluates unique circumstances and makes recommendations.

Responsibilities:

• Applies basic knowledge of the client's business need to formulate and define analytic objectives. Uses available data elements, defines business rules, and solution objectives.
• Develops, enhances and maintains a client's metadata based on analytic objectives. May load data into the infrastructure, creates hypothesis matrix, and identifies available data to prepare for the Exploratory Data Anlysis (EDA) and hypotheses.
• Builds models to supports/contribute to the overall solution, validates initial model and validates results & performance after the implementation.
• Researches, identifies, and aids in delivering data science solutions to problem domain. Contributes significantly in measurement of business performance based on the model deployed. If needed, leads the model enhancements.
• Create visualization of the model's insights for easy consumption.
• Collaborate with worldwide stakeholders.

What you will Bring:

Education and Experience Required:

Master´s degree in Statistics, Operations Research, Computer Science or equivalent preferred. Or Bachelor´s Degree in these areas and at least 2-3 years of relevant experience.

Knowledge and Skills:

• Working knowledge of data science methodologies including, but not limited to classical regression, neural nets, CHAID, CART, association rules, sequence analysis, cluster analysis, and text mining.
• Understanding of business requirements, how they relate to data science objectives and how to translate them into mathematical models.
• Strong background and working proficiency in effective use of analytics software (eg. Python, R, SAS, ).
• Working knowledge of machine learning, data integration, and modeling skills and ETL tools (eg. Dataiku, Infomatica, Ab Initio, Talend).
• Solid communication and presentation skills.
• Working knowledge of relevant data programming languages and relevant libraries (eg. Python, SQL, R, etc).
• Strong interpersonal skills and effectiveness in working across geographical boundaries.
• Working knowledge of data visualization techniques and tools (eg. PowerBI, Tableau, Excel, etc).

Additional Skills:

Accountability, Accountability, Action Planning, Active Learning, Active Listening, Agile Methodology, Agile Scrum Development, Analytical Thinking, Bias, Coaching, Creativity, Critical Thinking, Cross-Functional Teamwork, Data Analysis Management, Data Collection Management, Data Controls, Design, Design Thinking, Empathy, Follow-Through, Growth Mindset, Intellectual Curiosity, Long Term Planning, Managing Ambiguity, Market Analysis {+ 5 more}

What We Can Offer You:

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.

Diversity, Inclusion & Belonging

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

HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT and Affirmative Action employer. We are committed to diversity and building a team that represents a variety of backgrounds, perspectives, and skills. We do not discriminate and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global diverse team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.

Hewlett Packard Enterprise is EEO F/M/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.