EBP AI/ML Data Scientist
Company Name:-
HP
Job Location:-
Bengaluru, Karnataka
Job Summary:-
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 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 Data Scientist 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.
The specific responsibilities of the role:
Pipeline deployment maintenance, due to:
Bad results after training
Code error during execution
Invalid data set during execution
Schedule not running
Data ingestion pipeline maintenance, due to:
Network issues
Credential issues
Data inconsistency
Infrastructure resou
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