Data Scientist- Telecom domain

Data Scientist Telecom Domain

Experience: 4+ Years
Location: Remote
Industry: Telecom / AI-ML / Data Science

Job Summary

We are looking for an experienced Data Scientist / ML Engineer with strong expertise in Python, statistics, machine learning, graph analytics, anomaly detection, and large-scale data processing.

The role involves building advanced AI/ML and Data Science solutions on Telecom OSS data, including network alarms, events, configuration, performance counters, topology, tickets, logs, and security-related data.

You will work on solutions for network reliability, proactive fault management, service assurance, operational efficiency, Root Cause Analysis (RCA), and automated decision-making.

Key Responsibilities

• Analyze high-volume telecom event streams using statistical correlation and association techniques.
• Apply PMI/NPMI, Jaccard, Lift, and co-occurrence analysis to identify related events and suppress redundant alerts.
• Develop graph-based solutions using NetworkX / igraph and community detection algorithms.
• Apply Louvain, Leiden, and Label Propagation techniques for network structure discovery.
• Develop clustering and pattern-mining solutions for recurring fault signatures.
• Implement K-Means, DBSCAN/HDBSCAN, hierarchical clustering, Apriori, and FP-Growth.
• Build anomaly detection solutions for bursts, flapping/oscillating events, and rare-event detection.
• Apply Isolation Forest, Robust Z-score, EWMA, and change-point detection.
• Develop temporal and causal models for fault propagation and Root Cause Analysis.
• Design model evaluation methodologies and proxy ground truth where labeled data is unavailable.
• Benchmark competing algorithms and select solutions based on quantitative evidence.
• Build scalable data pipelines for production-scale telecom datasets.
• Work with engineering teams to move models from prototype to production.
• Read research papers and implement algorithms into tested, production-ready code.
• Prepare technical design documents, benchmarking reports, and validation reports.

Required Skills

• 4+ years of experience as a Data Scientist or ML Engineer.

• Expert-level Python programming.

• Strong knowledge of statistics and unsupervised learning.

• Strong experience with:

• Python

• NumPy

• SciPy

• Pandas / Polars

• PyArrow

• Scikit-learn

• HDBSCAN

• NetworkX / igraph

• PostgreSQL / SQL

• AWS S3

• Parquet

• pytest

• Hands-on experience with graph analytics and community detection.

• Strong understanding of clustering, anomaly detection, association mining, and pattern mining.

• Experience with large-scale tabular, time-series, and event-driven datasets.

• Ability to optimize memory and runtime for large datasets.

• Ability to independently frame problems and select appropriate algorithms.

Telecom Domain Experience

Candidates with experience in Telecom OSS, Network Analytics, Network Management, Service Assurance, Fault Management, or Network Operations will be preferred.

Exposure to:

• Network alarms
• Network events
• Configuration data
• Performance counters
• Network topology
• Tickets
• Logs
• Security data
• FCAPS
• Root Cause Analysis

Good to Have

• Neo4j / Cypher / Neo4j GDS
• Temporal Point Processes / Hawkes Processes
• Causal Discovery
• Time-Series Anomaly Detection
• Telecom Network Fault Management
• Research-oriented algorithm implementation