Enterprise Business Planning Advance Analytics Intern

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 Advanced Analytics Intern will work closely with the EBP leadership team on driving some proofs-of-concept in the P&L forecasting space. This individual will direct the use of machine language and statistical modeling techniques to develop and evaluate algorithms to improve forecast accuracy. The results will be shared with the program management team for possible implementation.

Knowledge and Skills

• Knowledge of modern computer science including algorithms, data structures, software architecture. Able to architect new solutions that combine services, data preparation and pre-processing, machine learning models and data presentation.
• Familiarity with statistical modelling (esp. time-series forecasting) is required. Exposure to programming languages like Python and R is a plus.
• 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

Job -

Administration

Schedule -

Full time

Shift -

No shift premium (United States of America)

Travel -

No

Relocation -

Yes

EEO Tagline - 

HP Inc. is EEO F/M/Protected Veteran/ Individual with Disabilities.