# Applied Artificial Intelligence Data Scientist at HP

HP is hiring an Applied Artificial Intelligence Data Scientist in Bengaluru, India. Level rates it Builds AI ●●●●; you can [apply on HP](https://jobsbylevel.com/go/0a30c4ff-0e3b-42a0-8668-bea45ad9e13c?utm_medium=ai-agent).

AI Level 4, AI centrality 89 out of 100. Bengaluru, Karnataka, India.

## Details

- Company: [HP](https://jobsbylevel.com/companies/hp)
- AI level: AI Level 4 (score 89 out of 100)
- Location: Bengaluru, Karnataka, India
- Posted: October 21, 2026
- Apply: https://jobsbylevel.com/go/0a30c4ff-0e3b-42a0-8668-bea45ad9e13c?utm_medium=ai-agent

## Prepare for this job

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## Description

Applied Artificial Intelligence Data Scientist Description - AI Data Scientist – Quality Intelligence & Transformation Overview The Quality organization is seeking an AI Data Scientist to accelerate the transformation of quality operations through Artificial Intelligence, Machine Learning, Predictive Analytics, and Generative AI. This role will partner with Quality Program Managers (QPMs), Quality Engineers, Data Analysts, Service teams, Product teams, and Technology organizations to design, build, evaluate, and scale AI-powered solutions that improve product quality, customer experience, operational efficiency, and business decision-making. The ideal candidate combines strong technical expertise in Large Language Models (LLMs), Generative AI, Machine Learning, Predictive Analytics, and Data Science with an understanding of quality, reliability, service, and operational processes. Success in this role requires the ability to identify high-value business problems, translate them into scalable AI solutions, and drive measurable business outcomes. This position supports the Quality organization's vision of building AI-enabled capabilities that transform quality management from reactive monitoring to predictive quality intelligence. Key Responsibilities AI Solution Development Design, build, and deploy AI-powered solutions leveraging Large Language Models (LLMs), Generative AI, Machine Learning, Predictive Analytics, and AI Agents. Develop scalable AI solutions that automate quality analysis, issue detection, root-cause investigation, reporting, forecasting, and decision support. Build intelligent copilots and AI assistants that improve productivity for quality engineers, analysts, and program managers. Develop Retrieval-Augmented Generation (RAG) solutions leveraging quality documentation, knowledge repositories, and operational data. Predictive Quality Intelligence Develop predictive models for quality risk detection, intervention forecasting, anomaly detection, reliability analysis, and failure prediction. Create AI-driven early warning systems by integrating quality, service, telemetry, customer, warranty, and operational signals. Identify quality trends, emerging risks, and performance drivers through advanced analytics and machine learning. Support the organization's journey from reactive issue management to predictive quality management. Data Science & Analytics Analyze large-scale structured, semi-structured, and unstructured datasets to generate actionable insights. Develop data pipelines, feature engineering frameworks, and analytical workflows supporting AI initiatives. Consolidate data across multiple enterprise sources to create integrated quality intelligence platforms. Build statistical models, forecasting solutions, and advanced analytics frameworks to support business planning and operational excellence. AI Transformation & Automation Identify opportunities to automate manual quality processes through AI and intelligent automation. Lead AI pilot programs and proof-of-concepts from ideation through deployment. Establish reusable AI frameworks, templates, and best practices across the Quality organization. Drive adoption of AI technologies through training, enablement, and stakeholder engagement. Collaboration & Leadership Partner with Quality, Engineering, Services, ISX, Data & Analytics, and Business teams to define AI use cases and implementation roadmaps. Translate business requirements into technical solutions and clearly communicate findings to both technical and non-technical audiences. Present recommendations, insights, and business impact to senior leadership. Promote responsible AI practices, governance, and ethical AI adoption. Required Qualifications Bachelor's, Master's, or PhD in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, Engineering, Mathematics, or a related field. 3+ years of experience developing AI, Machine Learning, and Data Science solutions. Strong

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