Data Scientist

Data Scientist

  

This role has been designed as ‘Hybrid’ with an expectation that you will work on average 2 days per week 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:

   

The Data Scientist (AI Cloud Developer) builds scalable, data-driven solutions from the ground up to address mission-critical business challenges, continuously exploring innovative statistical, machine learning, and AI methodologies to deliver end-to-end analytical solutions that drive measurable business impact.

• Applies advanced analytical thinking to deconstruct complex, multi-dimensional datasets and engineer novel algorithms, models, and methodologies for solving business problems—from initial exploratory data analysis through prototyping, model development, validation, and production deployment of ML/AI solutions.
• Collaborates cross-functionally with data engineers, MLOps teams, product managers, and business stakeholders to ensure robust model performance, efficient pipeline orchestration, continuous monitoring, and sustainable operationalization of data science solutions at scale.
• Delivers quantifiable business value by developing innovative data products, predictive models, and analytical frameworks that enhance HPE's data science capabilities across diverse domains, platforms, and use cases—translating complex insights into actionable recommendations that drive strategic decision-making.

Management Level Definition:

Contributions impact technical components of HPE products, solutions, or services regularly and sustainable. Applies advanced subject matter knowledge to solve complex business issues and is regarded as a subject matter expert. Provides expertise and partnership to functional and technical project teams and may participate in cross-functional initiatives. Exercises significant independent judgment to determine best method for achieving objectives. May provide team leadership and mentoring to others.

Responsibilities:

• Collaborate with cross-functional teams to design, develop, and implement cloud solutions tailored to meet business needs.
• Work with domain experts to identify and formalize machine learning problems for wireless and wired network diagnostics, root causing, problem remediation, and optimization
  • Design, implement, and validate machine learning algorithms on big data
  • Guide and oversee deployment of implemented machine learning solutions and monitor their operation
  • Use Agentic AI to solve networking problems
• Identify, debug and create solutions for issues with code and integration into application architecture
• Develop and execute comprehensive test plans for features adhering to performance, scale, usability, and security requirements.
• Deploy cloud-based systems and applications code using continuous integration/deployment pipelines
• Contribute towards innovation and integration of new technologies into projects
• Analyze science, engineering, business, and other data processing problems to develop and implement solutions to complex application problems, system administration issues, or networking

Education and Experience Required:

• Master's or PhD degree in computer science, data science, mathematics, physics, statistics, physics, or closely related quantitative discipline.
• Typically, 3-4 years’ experience working as a Data Scientist building products /features using machine learning, deep learning and generative AI

Knowledge and Skills:

• Strong background in statistical and machine learning techniques such as anomaly detection, clustering and ranking of events, time series analysis, hypothesis testing, causal inference, deep learning and reinforcement learning, semi-supervised learning, or mixed time-series/event streams
• Experience with GenAI and large language models (LLMs). Agentic AI is a plus
• Familiarity with and understanding of design for software systems
• Proficient Python coder (PySpark, Scikit-learn), experience with software engi