Senior Data Scientist (AI/ML) Job at Hewlett Packard Enterprise (Bangalore)

Senior Data Scientist (AI/ML)

Hewlett Packard Enterprise

Location:
India , Bangalore

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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Job Description:

Senior Data Scientist (AI/ML). This role has been designed as ‘Hybrid’ with an expectation that you will work on average 2 days per week from an HPE office. 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 Responsibility:

Leads as well as develops scalable AI solutions using relevant AI (ML/DL/Gen AI) techniques
Architects large scale AI solutions that seamlessly merge AI model and techniques in SDLC
Organizes and leads comprehensive code and design review sessions, driving discussions to align with project requirements and best practices. Mentor and provide feedback to junior and mid-level team members
Conducts research and stays up to date with the latest advancements in AI and machine learning technologies, frameworks, and algorithms. Explore and experiment with cutting-edge techniques to solve complex problems and improve existing models
Collaborates with cross-functional teams to understand business requirements and design AI and machine learning solutions. Determine the appropriate algorithms, models, and frameworks to use and architect the overall system to ensure scalability, efficiency, and robustness
Develops, implements, and optimizes machine learning models and algorithms. This includes data pre-processing, feature engineering, model selection, hyperparameter tuning, and training on large datasets. Continuously monitor and improve model performance and accuracy
Leverage or build analytics tools that utilize the data pipeline to provide significant insights into customer case data, bug data, operational and other key business performance metrics
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources
Work with data and analytics specialists to strive for greater functionality in our data systems
Identify trends, patterns from dataset to scope opportunities for automation
Deploys machine learning models into production environments, considering scalability, performance, and security considerations. Integrate models with existing software systems and infrastructure, ensuring smooth operation and interoperability
Monitors the performance of deployed models, collects relevant metrics, and analyzes data to identify areas for improvement. Based on insights gained from monitoring and analysis, fine-tune models, optimize algorithms, and enhance system performance
Works collaboratively with the engineering manager and team lead to set design and implementation standards, ensuring continuous improvement and alignment with project goals
Regularly leads meetings, fostering a collaborative and productive team environment
Has experience in providing technical leadership, mentorship, and guidance to junior team members
Address and resolve challenges proactively
Develops and delivers strategic presentations and reports to senior stakeholders, demonstrating a deep understanding of technical and business aspects. Provide insights and recommendations
Applies and leverages data mining, data modeling, natural language processing, and machine learning to extract and analyze information from datasets

Requirements:

9+ years of experience in a Data science role
Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field
5+ years experience building data pipelines for data science-driven solutions and deployed in Production environment
Experience working in technical support environment, working with dataset from CRM, H/W and S/W bugs data, machine logs
Experience supporting and working with multi-functional teams in a multidimensional fast paced environment
Good team worker with excellent interpersonal, written, verbal and presentation skills
Experience building and optimizing data pipelines, architectures and data sets
Experience performing root cause analysis on internal and external data and processes
Strong analytic skills related to working with unstructured datasets
Build processes supporting data transformation, data structures, metadata, dependency and workload management
A successful history of manipulating, processing and extracting value from large, disconnected datasets
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Strong hands-on coding skills (preferably in Python) processing large-scale data set and developing machine learning model
A strong foundation in mathematics and statistics. In-depth knowledge of linear algebra, calculus, probability theory, and statistical concepts
Good knowledge on Software Development Life Cycle and Agile principles
Experience working with Large Language models, Generative AI, Conversational AI
Familiar with one or more machine learning or statistical modeling tools such as Numpy, ScikitLearn, MLlib, Tensorflow, NLP libraries
Experience working with Databricks, Snowflake platforms
Experience with AWS, S3, Spark, Kafka, Elastic Search
Experience with big data tools: Hadoop, Spark, Kafka, etc.
Experience with relational SQL and NoSQL databases, including Postgres and Cassandra
Experience with data pipeline and workflow management tools
Experience with AWS cloud services: EC2, EMR, RDS, Redshift
Experience with stream-processing systems: Storm, Spark-Streaming, etc.

Nice to have:

Accountability
Action Planning
Active Learning
Active Listening
Agile Methodology
Agile Scrum Development
Analytical Thinking
Bias
Coaching
Creativity
Critical Thinking
Cross-Functional Teamwork
Data Analysis Management
Design
Design Thinking
Empathy
Follow-Through
Group Problem Solving
Growth Mindset
Long Term Planning
Managing Ambiguity

What we offer:

Health & Wellbeing
Personal & Professional Development
Unconditional Inclusion

Additional Information:

Job Posted:
January 13, 2026

Work Type:

Hybrid work

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