Translate business needs into technical requirements and define model objectives, input data, and success metrics.
Design, develop, and deploy end-to-end machine learning models (Supervised, Unsupervised, and Reinforcement Learning) to solve complex telco challenges
Apply AI/ML techniques to improve network performance and customer experience
Build and maintain scalable data pipelines and feature stores using cloud platforms to ensure seamless model training and inference at scale.
Partner with Network, Technology, and Commercial teams to translate business requirements into technical AI roadmaps and provide actionable insights that drive excellent experience, revenue or cost efficiency.
Design and execute rigorous experimentation frameworks to validate model performance and business impact, ensuring high accuracy and model stability over time.
Requirements
Technical Skills:
Bachelor's or Master's degree in Computer Science, Information Technology, Statistics or related field.
Minimum of 3–6 years of professional experience in Data Science or Machine Learning, particularly in projects involving AI and machine learning with a proven track record of designing and implementing data pipelines and architecture including data ingestion, processing and delivery.
Expert-level programming in Python
Hands-on experience designing multi-agent systems and orchestration frameworks (e.g., Google ADK, LangChain, AutoGen, or CrewAI)
Hands-on experience with ML frameworks such as XGBoost, Scikit-learn, TensorFlow, or PyTorch
Strong command of SQL and experience with big data technologies (e.g., BigQuery, Spark)
Familiarity with Telco-specific data structures, network KQIs and subscriber behavioral patterns
Familiarity with cloud platforms like Google Cloud Platform (GCP) and their associated data services
Familiarity with MLOps lifecycle (CI/CD for ML).
Familiarity with ETL tools like Apache Airflow or Talend
Professional certifications such as Google Professional Machine Learning Engineer or similar are highly regarded.
Soft Skills :
Strong analytical and problem-solving abilities.
Excellent communication and teamwork skills to collaborate effectively with various teams.
Ability to explain complex technical concepts to non-technical stakeholders and a proactive, problem-solving mindset.
Ability to work independently in a dynamic environment.
