Data Scientist

We are looking for a talented Senior Data Scientist to join a leading multinational group in the Telecommunications and Technology sector. This role offers the exciting opportunity to drive key initiatives in predictive modeling, financial analytics, and Agentic AI development to transform the way businesses make data-driven decisions.

Key Responsibilities

• Design and implement predictive models for revenue/cost forecasting, churn prediction, cost optimization, and financial risk analysis.
• Develop and deploy Agentic AI systems for autonomous decision-making and multi-agent collaboration.
• Collaborate with cross-functional teams (Finance, Operations, Product) to translate business needs into actionable data solutions.
• Lead experimentation and validation using real-world telecommunications datasets.
• Drive the strategic roadmap for AI-powered financial transformation.

Required Skills & Experience

Education:

• Master’s or PhD in Data Science, Computer Science, Engineering, Statistics, Mathematics, or Physics.

Technical Skills:

• Expertise in advanced time series analysis (ARIMA, Exponential Smoothing, etc.).
• Strong background in AI & Machine Learning models (Regression, Clustering, Neural Networks, SVMs).
• Experience with econometrics, optimization models, and multimodal AI architecture.
• Python, PySpark, SQL, and experience with ML frameworks.
• Familiarity with cloud platforms (preferably Azure) and MLOps practices (CI/CD, Git).
• Understanding of telecommunications financial structures (ARPU, OPEX/CAPEX).

Soft Skills:

• Strategic thinking with a focus on aligning data science with business goals.
• Exceptional communication skills to translate complex models into actionable insights.
• Strong leadership and mentorship capabilities to guide junior team members.
• Ability to adapt and thrive in a fast-paced, evolving environment.

Why Join Us?

• Cutting-edge AI initiatives in a global technology leader.
• Opportunities for career growth, leadership, and impactful work.
• Competitive compensation and a hybrid work environment.