Applied Artificial Intelligence Data Scientist
HP Inc. (company site, opens in a new tab)3+ yrsBengaluruOn-siteDirect career pageEst. 14–30 LPA
Posted 14h ago
Reach people at HP Inc.
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at HP Inc. you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Design, build, and deploy AI-powered solutions leveraging LLMs, Generative AI, ML, Predictive Analytics, and AI Agents to enhance quality operations.
- Develop predictive models and AI-driven early warning systems for quality risk detection, anomaly detection, and failure prediction.
- Lead AI transformation initiatives including automation of quality processes, pilot programs, and scalable AI frameworks across the Quality organization.
Minimum Requirements
- Bachelor's, Master's, or PhD in Computer Science, Data Science, AI, ML, Statistics, Engineering, Mathematics, or related field.
- 3+ years of experience in developing AI, Machine Learning, and Data Science solutions.
- Strong proficiency in Python and AI/ML frameworks; experience with large-scale datasets using SQL, Spark, Databricks, or equivalent.
- Understanding of statistical modeling, experimentation, model evaluation, and validation methodologies.
Ideal Candidate Profile
- Hands-on experience with Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), and AI agents.
- Demonstrated ability to translate complex business problems into scalable AI solutions with measurable business impact.
- Experience working collaboratively in cross-functional, geographically distributed teams to drive AI adoption and quality transformation.