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Hewlett Packard Enterprise Logo Hewlett Packard Enterprise · IT - Software Development

Senior Data Scientist

India, Bangalore · Job Posted January 15, 2026
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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.

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
  • 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
  • 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.

What we offer

  • Health & Wellbeing
  • Personal & Professional Development
  • Unconditional Inclusion
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