GM - Data Scientist
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Job Description
Role
GM – Data Scientist
Job Level/ Designation
M3/GM
Function / Department
SNOC
Location
Pune
Job Purpose
Own the AI/ML roadmap and lead technical strategy for large-scale telecom analytics KPI prediction, anomaly detection, RCA automation, log intelligence, LLM-based systems, and predictive maintenance.
Key Result Areas/Accountabilities
Bachelors or Master's degree in Computer Science, Engineering, or related fields from premier institutions (IITs, NITs, BITS, or equivalent Tier-1 colleges)
GM – Data Scientist
Job Level/ Designation
M3/GM
Function / Department
SNOC
Location
Pune
Job Purpose
Own the AI/ML roadmap and lead technical strategy for large-scale telecom analytics KPI prediction, anomaly detection, RCA automation, log intelligence, LLM-based systems, and predictive maintenance.
Key Result Areas/Accountabilities
- Define AI/ML architecture, modeling frameworks, and experimentation strategy.
- Lead DS teams, review designs, experiments, and validations.
- Architect ML systems for real-time diagnostics and forecasting.
- Solve complex network behavior issues with spatial temporal ML.
- Build scalable pipelines on enterprise VMs.
- Translate network issues into ML solutions.
- Own model governance, drift controls, and explain ability.
- Advanced ML: probabilistic models, anomaly detection, clustering.
- Deep Learning: LSTM, Transformers, embeddings.
- NLP: log classification, embeddings, similarity search.
- Math/Stats: optimization, time-series decomposition.
- Programming: Python expert.
- Telecom Analytics: KPI degradation, syslog/ISE analysis.
- MLOps: MLflow, Airflow, onprem deployments.
- GENAI, Agentic AI
Bachelors or Master's degree in Computer Science, Engineering, or related fields from premier institutions (IITs, NITs, BITS, or equivalent Tier-1 colleges)
More Info
Key Skills
LSTM
Math Stats optimization
Time-series decomposition
Syslog ISE analysis
MLflow
Similarity search
GENAI
Advanced ML probabilistic models
Embeddings
Agentic AI
Log classification
Telecom Analytics
KPI degradation
