Applied Artificial Intelligence Data Scientist

Role Overview

The Quality division is seeking a skilled AI Data Scientist to spearhead the integration of Artificial Intelligence, Machine Learning, Predictive Analytics, and Generative AI within quality operations. This role involves close collaboration with Quality Program Managers, Engineers, Data Analysts, and various technology and product teams to conceptualize, build, assess, and expand AI-driven applications that enhance product quality, customer satisfaction, efficiency, and strategic decision-making.

Key Responsibilities

• Design, develop, and implement AI solutions employing Large Language Models, Generative AI, predictive analytics, and autonomous AI agents.
• Create scalable automation tools for quality monitoring, issue detection, root-cause analysis, reporting, forecasting, and decision support.
• Develop AI-powered digital assistants to boost productivity for quality teams.
• Utilize Retrieval-Augmented Generation techniques utilizing quality and operational data repositories.
• Construct predictive models for detecting quality risks, forecasting interventions, identifying anomalies, and analyzing reliability and failure patterns.
• Integrate diverse data signals to build AI early warning mechanisms.
• Analyze multi-disciplinary datasets to derive actionable intelligence and support quality management transformations.
• Lead AI pilot projects from concepts to deployments, create reusable AI frameworks and promote AI adoption across the organization.
• Engage with stakeholders to define use cases, translate business needs to technical solutions, communicate insights, and advocate responsible and ethical AI applications.

Requirements

• Bachelor's, Master's, or PhD in Computer Science, Data Science, AI, Machine Learning, Statistics, Engineering, Mathematics, or related disciplines.
• Minimum 3 years developing AI, machine learning, and data science solutions.
• Proficient in Python and modern AI/ML frameworks and tools.
• Expertise in predictive modeling, developing machine learning workflows, and handling large-scale enterprise datasets using SQL, Spark, Databricks, or similar platforms.
• Solid understanding of statistical modeling techniques, experimentation, and model evaluation.
• Capacity to thrive within cross-functional and geographically diverse teams with strong analytical, problem-solving, and communication capabilities.
• Preferred candidates have 5+ years in enterprise AI development and experience with cloud AI services (Azure AI, OpenAI, AWS, GCP), Generative AI, LLMs, RAG, prompt engineering, AI agents, knowledge graphs, Power BI, Fabric, Databricks, MLOps, AI governance, and familiarity with quality management and related analytics domains.

Success Criteria

• Delivers AI solutions that significantly enhance quality outcomes, productivity, and operational efficiency.
• Builds predictive intelligence capabilities for earlier risk detection and issue identification.
• Develops widely adopted AI copilots and automation tools for quality teams.
• Transforms business challenges into actionable AI applications that realize measurable impact.
• Drives AI adoption and daily usage across teams, establishing scalable frameworks and standards.
• Exhibits strong ownership, innovation, and collaboration across organizational boundaries.

Core Competencies

• Applied artificial intelligence and machine learning
• Large language models and generative AI
• Predictive quality analytics and early warning systems
• Data science, statistical modeling, and experiment design
• AI agents, intelligent automation, and business problem-solving
• Cross-functional collaboration and executive communication

Equal Opportunity Statement

HP is committed to providing equal employment opportunities to all individuals regardless of race, color, religion, sex, national origin, sexual orientation, age, disability, veteran status, or any legally protected status. Information voluntarily disclosed by applicants will remain confidential and is not used adversely.