Enterprise Business Planning Business Analytics Intern

Key Skills

Algorithms, AzureML, Calculus, Continuous Integration & Continuous Delivery - CI/CD, Data Engineering, Data pipelines, Data structuring, DevOps, Linear Algebra, Machine learning techniques, Statistical modeling

Job Description

At HP, we believe in the power of ideas. Our vision is to create technology that makes life better for everyone, everywhere — every person, every organization, and every community around the globe. This motivates us — inspires us — to do what we do. To make what we make. To invent, and to reinvent. To engineer experiences that amaze.

In the Transformation Organization (TO), we are looking for visionaries who are willing to push boundaries to help us rewrite the rules for HP Inc. The TO will accelerate transformation through embracing agile new ways of working, investing in the digital literacy of our workforce, and using the power of data, AI, automation, and robotics to extract cost and complexity from across our business.

The Enterprise Business Planning (EBP) program is transforming how HP does enterprise-wide planning and forecasting, from WW LTP to weekly account planning in countries. This effort is multi-dimensional in nature, including (1) elements of organizational design, (2) process redesign, (3) applying sophisticated technology and application tools, and (4) leading advanced change management techniques to deliver the full value of large-scale transformation.

The EBP AI/ML Ph.D. Intern will work closely with the EBP Data Architect and consulting partner to drive technical leadership and oversight of the development of integrated software algorithms to structure, analyze and leverage data in product and systems applications for the EBP program. This individual will direct the use of machine language and statistical modeling techniques develop and evaluate algorithms to improve performance, quality, data management and accuracy.

This individual must be capable of working independently in understanding the role requirements and delivering to them. The person will be expected to work on complex problems and in some cases, act as a consultant on other AI/ML/ data engineering projects within the team.

Education and Experience Required

• Bachelor’s degree working towards completion of Ph.D. program in Computer Science, Statistics, and/or Math or equivalent, demonstrated through work experience, journal and/or conference publications or open-source projects

Knowledge and Skills

• Knowledge of Cloud – AzureML, AzureDevOps, Testing, Data Engineering, CI/CD processes, Software Deployment, ML pipeline/solution lifecycle
• Knowledge of modern computer science including algorithms, data structures, software architecture. Where applicable, knowledge of cloud and hybrid cloud service architectures and their impacts on development and deployment. Able to architect new solutions that combine services, data preparation and pre-processing, machine learning models and data presentation.
• Knowledge of the Mathematics of Machine Learning (particularly Linear Algebra, differential calculus) and Statistics
• Deep understanding of current machine learning algorithms, under which circumstances each is applicable and their pros and cons. Able to compose new model architectures and objective functions
• Knowledge of data processing techniques and data pre-processing requirements for the common machine learning approaches. Knowledge of data collection techniques. Knowledge of data augmentation approaches and their pros and cons