Gartner Hiring Drive 2024: Gartner Hiring Drive 2024 for its Data Analyst. Gartner Drive organizes off-campus drives for candidates in any batch. To apply, candidates should have a Graduation in Engineering, Math, or Statistics. if you are interested, please apply as soon as possible.
Company Name: Gartner
Role: Data Analyst
Location: Gurugram
Experience: 1 – 4 years
Qualification: Graduation in Engineering, Math or Statistics
Batch: Any
Job Type: Full Time
Salary: 10.2 LPA (Expected)
Gartner Hiring Drive 2024
Job Description:
- The Service Operations Centre of Excellence in Gurgaon is responsible for ensuring global Client retention.
- The Advanced Analytics team within Service Operation group generates valuable insights by interpreting large volumes of data for Service Delivery associates and their leaders around new ideas, opportunities, and strategies on the way we engage clients, leading to higher client retention.
Requirements:
- Graduation in Engineering, Math or Statistics with 1 – 4 years in business analytics
- Experience with advanced data manipulation and summarization skills using Excel/Python
- SQL knowledge to fetch relevant data from warehouse
- Intermediate PowerBI knowledge to leverage it as a tool to manipulate large size datasets
- PowerPoint skills including ability to summarize key message and leverage right charts in think-cell
- Demonstrated expertise in descriptive analytics and statistical analyses as good to have
Responsibility:
- Identify, track, measure and report metrics that impact client retention and drivers of retention and work with automation team to efficiently scale reporting
- Identify retention opportunities through analytical approaches and arrive at recommended actions for service teams
- Influence senior internal stakeholders of BUs on prioritizing the right problems and to jointly implement initiatives
- Solve bugs and data quality issues by proactive collaboration with stakeholders and partners to fix data issues or integrate data into analytics system
- Enable automation opportunities as required
- Own process and systems improvement in different stages of data pipeline
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