Data Analyst

What the Team Works On The team develops AI/ML solutions for wireless network performance, including: • KPI anomaly detection engines • Root Cause Analysis (RCA) tools • FOA (First Office Application) performance analysis • Software release validation • Statistical comparison of pre- and post-software upgrades • Predictive analytics • Time-series forecasting • Automated identification of degraded cell sites • Correlation of KPI degradation with alarms, configuration changes, and software updates Day-to-Day Responsibilities The selected candidate will primarily: • Analyze very large telecom datasets • Build machine learning models • Develop anomaly detection algorithms • Perform statistical analysis and A/B testing • Create predictive models • Explore large datasets to identify trends • Build dashboards and reporting solutions • Collaborate with RF Engineers and RAN SMEs • Research new ML techniques and implement best practices • Develop automation tools for network performance analysis Ideal Candidate Profile The Hiring Manager is looking for someone with strong expertise across multiple disciplines. Machine Learning • Autoencoders • Transformers • Decision Trees • Neural Networks • Time Series Forecasting • ARIMA • Granger Causality • Supervised and Unsupervised Learning • Statistical Modeling • A/B Testing • Z-score Analysis Data Science • Data exploration • Feature engineering • Predictive modeling • Large-scale data processing • Research-oriented mindset • Ability to choose the right model for the right dataset Big Data • High-volume telecom datasets • Time-series data • Multivariate data analysis • KPI analytics • Large-scale data processing Technical Skills Must Have • Python (primary programming language) • Machine Learning • Artificial Intelligence • Data Modeling • Statistics • Time Series Analysis • AWS • Databricks • Linux • SQL • Strong research mindset