5–7 yrsBengaluruOn-siteDirect career pageEst. 22–38 LPA
Posted on 25 Sept
Reach people at Hewlett Packard Enterprise (HPE)
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Hewlett Packard Enterprise (HPE) you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Develop and implement advanced data collection, analysis, and machine learning solutions to optimize digital customer experiences and business outcomes in networking support services.
- Collaborate with cross-functional teams including data engineering and business units to build scalable data models, analytics solutions, and dashboards using platforms like Power BI and Databricks.
- Lead efforts in discovering user behavior patterns, process improvements, and support training and mentoring of junior data scientists within the Digital Experience & Automation team.
Minimum Requirements
- Master’s or PhD degree in business administration, economics, computer science, management information systems, or related field or equivalent experience.
- 5-7+ years of experience in Data Science, Machine Learning, or Applied Research focused on measurement frameworks or systems.
- Expertise with statistical analysis, machine learning algorithms (clustering, regression, dimensionality reduction), and advanced analytics tools including Python, Snowflake, Databricks, and Power BI.
- Hybrid work model requiring approximately 2 days per week onsite at HPE office (location: Not explicitly mentioned in the JD).
Ideal Candidate Profile
- Experienced in applying machine learning to real-world business problems involving customer journey analytics, conversational AI data, and omnichannel support metrics.
- Skilled at collaborating across multiple teams including technology providers, engineering, and business stakeholders to drive data-driven decision making and automation.
- Proficient in designing and operationalizing measurement frameworks, experiments, and advanced visualization techniques to communicate insights effectively to both technical and non-technical audiences.