Data scientist Specialist

This role has been designed as ‘Hybrid’ with an expectation that you will work on average 2-3 days per week from an HPE office.

Job Description:

HPE Services is our innovative IT services organization. It provides the expertise to advise, integrate, and accelerate our customers’ outcomes from their digital transformation. Our teams collaborate to transform insight into innovation. In today’s fast paced, hybrid IT world, being at business speed means overcoming IT complexity to match the speed of actions to the speed of opportunities. Deploy the right technology to respond quickly to market possibilities. Join us and redefine what’s next for you.

What you’ll do:

Collaborate with cross-functional teams to identify opportunities for AI and Data to solve business challenges
• Design and implement data pipelines to collect, process, and integrate data from various sources
• Develop and optimize machine learning and deep learning models for predictive analytics, computer vision, natural language processing, and more
• Leverage big data technologies like Hadoop, Spark, and NoSQL databases to handle large-scale datasets
• Explore and apply generative AI techniques to generate synthetic data, create content, and automate tasks
• Implement MLOps practices to streamline the model development lifecycle and enable continuous deployment
• Present findings and recommendations to stakeholders in a clear and compelling manner
• Lead cross-functional teams to deliver AI projects on time and within budget
• Stay current with the latest advancements in AI, data engineering, and related technologies

Skills
• 8+ years of experience in data science, machine learning, and AI
• Proficiency in Python, SQL and data visualization tools like Tableau or PowerBI
• Hands-on experience with machine learning frameworks like TensorFlow, PyTorch, or Keras
• Knowledge of deep learning architectures and techniques for computer vision, NLP, and generative AI
• Hands-on experience with big data technologies such as Hadoop, Spark, and NoSQL databases
• Understanding of MLOps principles and tools for model versioning, monitoring, and deployment
• Familiarity with Kubernetes core concepts like pods, deployments, services, and ingress
• Strong communication and leadership skills to effectively collaborate with cross-functional teams
• Ability to work in a fast-paced, agile environment and adapt to changing priorities
•

What you need to bring:

Educational Qualification – Bachelor/Masters in technical field or equivalent experience.

Accountability, Accountability, Active Learning, Active Listening, Bias, Business Growth, Client Expectations Management, Coaching, Creativity, Critical Thinking, Cross-Functional Teamwork, Customer Centric Solutions, Customer Relationship Management (CRM), Design Thinking, Empathy, Follow-Through, Growth Mindset, Information Technology (IT) Infrastructure, Infrastructure as a Service (IaaS), Intellectual Curiosity, Long Term Planning, Managing Ambiguity, Process Improvements, Product Services, Relationship Building {+ 5 more}

Health & Wellbeing

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

Personal & Professional Development

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.

Diversity, Inclusion & Belonging

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know diverse 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.

#india

#servicesandsupport

Job:

Services

Job Level:

TCP_05

Hewlett Packard Enterprise is EEO F/M/Protected Veteran/ Individual with Disabilities.

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.