Data Scientist - RAN exp is must

Job Responsibilities:

• Hands-on developer in building models in complex data environments with unambiguous requirements and enjoys data.
• Advance causal inference techniques to improve outage predictions measurement, including uplift modeling, propensity scoring, and Bayesian methods.
• Develop forecasting models to predict outages performance, resource allocation impacts, and long-term customer impacts for operations teams.
• Enhance ad testing methodologies, including A/B testing, synthetic control experiments, and incrementally testing, to measure efficiency accurately.
• Optimize operational team decisioning, using reinforcement learning, Bayesian optimization, and econometric modeling.
• Work closely with data engineers to scale and automate model deployment, integrating ML solutions into production environments.

Required Qualifications:

• Bachelor's Degree Quantitative Field (math, statistics, economics, computer science, physics, engineering, etc.) (Required)
• Master's/Advanced Degree Quantitative Field (math, statistics, economics, computer science, physics, engineering) (Preferred)
• Proven experience in Fault Prediction models, with a focus on attribution modeling, causal inference, and model mix optimization.
• Strong background in machine learning, fault metrics, and statistical modeling RAN applications.
• Expertise in Python, SQL, and cloud platforms (Azure, Snowflake, Databricks) for scalable modeling and data processing.
• Experience with experimental design and incrementality testing in telecom RAN networking subject areas.
• Ability to communicate complex data science concepts to both technical and non-technical stakeholders, influencing business decisions