Senior Data Analyst, Network Analytics & AI
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Protocol Intelligence
Data-driven signals on your job's competitivenessNiche telecom ML role at lesser-known company reduces applicant density despite general interest in data roles.
Strong telecom network analytics and 5G domain focus reduces cross-industry transferability.
Explicit 10+ years and multiple mandatory technical and ML skills create stringent filters.
Job Description
Structured overview of role & requirementsAbout This Role
Own end-to-end analytics of 5G/LTE network telemetry and operational data, transforming raw data into insights that enhance network reliability and customer experience.
Develop, validate, and deploy ML models for anomaly detection, KPI forecasting, and root cause analysis on network telemetry data.
Collaborate cross-functionally with engineering and product teams to integrate models into production pipelines, dashboards, and define key network metrics.
Minimum Requirements
Bachelor's or Master's degree in Computer Science, Statistics, Engineering, or related field.
10+ years total work experience with at least 5 years in data analytics and 2 years in a senior or lead role.
Proficient in SQL and Python (pandas, NumPy) working with large datasets, with strong skills in statistics, time-series analysis, and anomaly detection.
Hands-on experience with ML libraries (scikit-learn, XGBoost, statsmodels) and time-series forecasting or unsupervised anomaly detection methods.
Ideal Candidate Profile
Experienced in telecom network data analytics and familiar with 4G/5G KPIs and RAN concepts to contextualize analytics for network performance.
Capable of leveraging AI and LLM tools practically to accelerate analysis and automate insights throughout the data lifecycle.
Skilled collaborator who can work closely with engineering to transition data science models from notebooks to production at scale.