Senior Sales Intelligence Analyst
Hewlett Packard Enterprise (HPE) (company site, opens in a new tab)7+ yrsBengaluruOn-siteDirect career pageEst. 22–35 LPA
Posted on 18 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
- Own and enhance core sales reporting dashboards covering pipeline health, bookings, revenue, productivity, and cross-sell metrics ensuring accuracy and scalability.
- Apply advanced analytics, AI, and predictive modeling to improve sales forecasting accuracy and generate actionable insights for business stakeholders.
- Develop and operationalize AI and data science solutions for sales use cases, collaborating cross-functionally to drive adoption and measurable business impact.
Minimum Requirements
- Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Business Analytics, or related field; Master’s degree preferred.
- 7-10+ years of experience in Sales Analytics, Sales Operations, Business Intelligence, Data Science, or related analytical field.
- Proficiency with CRM and BI tools (e.g., Salesforce, Tableau, Power BI), strong SQL skills and Python for data analysis and modeling.
- Onsite work expectation at an HPE office (location in India not explicitly mentioned).
Ideal Candidate Profile
- Experienced in translating complex sales data into scalable AI-driven analytics and predictive models supporting revenue and forecasting.
- Strong background in statistical modeling, machine learning, and AI techniques applied practically to sales performance and pipeline management.
- Able to manage analytics initiatives independently while collaborating cross-functionally and mentoring junior team members.