Country
- India
- Working Schedule
- Full time
- Work Arrangement
- Hybrid
- Relocation Assistance Available
- No
- Posted Date
- 25-Mar-2026
- Job ID
- 16514
Description and Requirements:
MGCC GG 9 - Data Scientist
Position Title:
MGCC GG 9 - Data Scientist
- Function, Responsibility Level:_
Reports to (Responsibility Level): GG 11 or above
Supervises:
Location:
Global Grade: 9
Cost Center (85 series):
Complexity: OSTG
PID/s Load Mapping:
Position Summary
MetLife established a Global capability center (MGCC) in India to scale and mature Data & Analytics, technology and operations capabilities in a cost-effective manner and make MetLife future ready. The center is integral to Global Technology and Operations with a focus to protect & build MetLife IP, promote reusability and drive experimentation and innovation. The Data & Analytics team in India mirrors the Global D&A; team with an objective to drive business value through trusted data, scaled capabilities, and actionable insights. The operating models consists of business aligned data officers
- US,
Japan and LatAm & Corporate functions enabled by enterprise COEs
- data engineering, data governance and data science
Role Value Proposition:
Data Scientist plays a critical role in data and analytics life cycle and significantly contributes to production grade data and analytics solutions. The role requires one to demonstrate analytical skills, machine learning. It is an individual contributor role under the guidance of senior colleagues
Responsibilities:
- Under the guidance of senior colleagues
- design, build, validate and deploy production grade rule-based & machine learning models using structured and unstructured data
- Perform exploratory data analysis, feature engineering
- Monitor, evaluate model performance.
- Ensure model development follows quality, security, compliance, explainability and responsible use of AI guidelines,
- Collaborate with multiple partners from Business, Technology, Operations
📌 Associate Data Scientist (Hyderabad)
🏢 MetLife
📍 Hyderabad
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