About this role
HP’s Enterprise Operations Applied AI organization seeks an AI Data Scientist to design, evaluate, deploy, and scale AI solutions that deliver measurable value across enterprise operations. The role combines applied research, machine learning engineering, data science, and business collaboration, with an emphasis on taking solutions beyond prototypes.
Responsibilities
- Develop AI solutions using large language models, generative AI, machine learning, and predictive analytics. Build supporting data pipelines, feature-engineering approaches, and analytical workflows.
- Research emerging AI methods and assess their applicability to enterprise problems. Design experiments to measure model effectiveness, accuracy, robustness, and operational performance.
- Analyze large-scale structured and semi-structured data, produce insights and predictive models, and support operational decisions.
- Translate business requirements into technical approaches; explain AI concepts to technical and non-technical audiences. Support adoption through training, demonstrations, documentation, and stakeholder engagement.
- Work with distributed engineers, data scientists, product owners, business leaders, and technology teams. Contribute reusable frameworks, best practices, and technical standards.
Required qualifications
A bachelor’s, master’s, or PhD in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, Engineering, Mathematics, or a related field; 3+ years developing AI, machine learning, and data science solutions; proficiency in Python and modern AI/ML frameworks; experience with model evaluation, experimentation, performance measurement, and validation; and analytical experience with large-scale tabular data using SQL, Spark, Databricks, or similar technologies. Candidates must be able to collaborate in culturally diverse, distributed teams.
Preferred qualifications
5+ years of relevant industry experience; cloud AI development with Azure, AWS, or GCP; GitHub and GitHub Copilot; retrieval-augmented generation, prompt engineering, and AI agents; and familiarity with MLOps, model monitoring, observability, and enterprise AI governance. Experience communicating with business stakeholders and working in matrixed organizations is also preferred.
The full-time position lists Spring and Austin, Texas. No travel is required. The US annual pay range is $130,700–$205,200, with potential bonus and/or equity; pay varies by location, skills, knowledge, and experience. Listed benefits include health, dental, vision, disability, and life insurance; an employee assistance program; a flexible spending account; 4–12 weeks of paid parental leave based on tenure; 11 paid holidays; and additional flexible paid vacation and sick leave.