Senior Data Scientist

Senior Data Scientist

  

This role has been designed as ‘’Onsite’ with an expectation that you will primarily work from an HPE office.

Who We Are:

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.

Job Description:

   

Are you looking for a unique, truly innovative role? What if it could be with one of the most impactful IT companies in the world? Then we have the right opportunity for you – we are looking for a Senior Data Scientist to work on evolving and shaping the AI/ML stack that powers the AI driven insights for software to manage compute devices from the edge to cloud. You will be a core partner to engineering, product and DevOps teams in shaping the core AI/ML infrastructure, models and pipeline that powers our product.

About the Team

The Core Services team for Compute Ops Management (COM) is the driving force behind the design and development of foundational services and private AI/ML infrastructure that powers HPE’s server management portfolio. We collaborate across engineering, design and product to deliver common services and infrastructure that allows our product feature teams to scale their feature delivery.

As a Data Scientist in the Core Services team, your primary focus areas will be:

Model development and deployment:

• Design, build, train, and fine-tune complex AI and machine learning models, including deep learning, natural language processing (NLP), and generative AI models like Large Language Models (LLMs).
• Develop Retrieval-Augmented Generation (RAG) and agentic workflows to enhance model accuracy and performance.
• Collaborate with machine learning engineers and DevOps teams to deploy AI models into production and establish MLOps best practices.
• Design and run A/B tests to measure model effectiveness in real-world scenarios.
• Focus on aligning our private on-premises AI/ML infrastructure buildout with the product features we want to support

Data analysis and management:

• Play a key role in understanding our data and help us unlock the potential of integrating robust and cost optimized  AI/ML techniques for training and inference to power innovations in our product’s feature set.
• Work with large, complex, and often unstructured datasets to develop data pipelines and prepare data for modeling.
• Conduct exploratory data analysis (EDA) to understand data patterns, distributions, and potential biases.
• Leverage synthetic data generation to augment datasets for model training.
• Ensure data quality and integrity throughout the data science lifecycle.
• Guide the definition of foundational data sets and develop metrics that inform key decisions
• Build forecasting and optimization models and establish source of truth dashboards and analyses that help us with capacity planning and drive partner teams to understand and improve infrastructure usage.

About you:

• Bachelor's or Master's degree in Data Science and./or Computer Science, or equivalent
• Typically 2-8 years’  experience in a quantitative role navigating ambiguous environments, ideally in infrastructure, systems or platform domains in an enterprise setting.
• Development experience with Python, Go or (Java, C#, C++, C) or similar programming languages
• Successful with big data, LLM and analytics
• Have an enthusiastic, go-for-it attitude. When you see something broken, you can’t help but fix it
• Have an urge to collaborate and communicate asynchronously
• Good understanding of distributed systems, event driven programming paradigms and designing for scale and performance
• Ability to troubleshoot complex issues with curiosity, flexibility, creativity and a sense of ownership and accountability 
• Strong communication skills and ability to work in a distributed team
• Highly desirable one or more of: Grafana, Prometheus, AWS, Kubernetes, Terraform

As a part of our team, you will be able to learn or apply existing knowledge in the following areas:

• Your contributions will hav