Data Scientist​/Machine Learning Engineer

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
• 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.

• Transformers
• Decision Trees
• Time Series Forecasting
• ARIMA
• Supervised and Unsupervised Learning
• Statistical Modeling
• A/B Testing
• Z-score Analysis

Data Science

• Predictive modeling
• Research-oriented mindset
• Ability to choose the right model for the right dataset