Data scientist

EstiaTech - Passion for Technology; Roma; In loco; EUR 45.000 - 70.000; Tempo pieno

Descrizione del lavoro

A consulting company in Rome is seeking a skilled Data Scientist to lead predictive modeling initiatives in the telecommunications sector. The ideal candidate will have expertise in AI and machine learning, strong programming skills in Python and SQL, and a deep understanding of financial structures. This role supports a hybrid work environment and offers an exciting opportunity to impact the future of data architecture.

Competenze

• Proficiency in advanced techniques in time series analysis.
• Strong experience in AI & Machine Learning Models.
• Knowledge of cloud platforms, Azure preferred.

Mansioni

• Design and implement analytical and predictive models.
• Develop and deploy Agentic AI systems.
• Collaborate with teams to translate business objectives into data-driven solutions.

Conoscenze

Time series analysis

AI & Machine Learning Models

Econometrics and optimization models

Model Evaluation and Validation

Python programming

SQL

Cloud platforms knowledge

Strumenti

PySpark

ML frameworks

Azure

Descrizione del lavoro

📍 Location: Rome / Hybrid

🏢 Azienda: Estiatech S.r.l. – Consulting and System Integration Company

🌐 Global team | Telecommunications & Technology

🌟 Position: Data Scientist

Estiatech Srl is partnering with a leading global group in the Telecommunications and Technology sectors to find a talented Senior Data Engineer. This is an exciting opportunity to join a Big Data division where you'll help drive the future of data architecture and solutions at scale.

Overview

A leading multinational group in the telecommunications and technology sector, is seeking a highly skilled and forward-thinking Data Scientist to lead initiatives in predictive modeling for telecommunications financials and Agentic AI development. This role combines deep statistical modeling expertise with cutting‑edge AI capabilities to drive strategic insights, automation, and intelligent decision‑making across financial operations and customer‑facing systems.

Key Responsibilities

• Design and implement analytical and predictive models for revenue / cost forecasting and management, churn prediction, cost optimization, and financial risk analysis.
• Develop and deploy Agentic AI systems capable of autonomous decision making and multi‑agent collaboration.
• Collaborate with finance, operations, and product teams to translate business objectives into data‑driven solutions.
• Ensure model interpretability, fairness, and regulatory compliance.
• Lead experimentation and validation cycles using real world telco datasets.
• Contribute to the strategic roadmap for AI driven financial transformation.

Required Technical Skills

• Proficiency in advanced techniques in time series analysis: ARIMA, Exponential Smoothing, Box Jenkins, etc.
• Proficiency in AI & Machine Learning Models: Regression Analysis, Scenario Analysis, Clustering & Segmentation, Random Forests & Decision Trees, Neural Networks (RNN, LSTM), Support Vector Machines (SVM), etc.
• Knowledge of econometrics and optimization models: Linear and Nonlinear Programming optimization, Stochastic optimization, Metaheuristics optimization, Vector Autoregression (VAR), Mixed-Integer Optimization, etc.
• Strong Experience in Model Evaluation and Validation: Cross‑Validation, Performance Metrics, Overfitting & Regularization, etc.
• Ability to architect and train multimodal AI agents: implement agentic solutions using LLMs, simulation environments, and planning frameworks. Hands‑on experience with Agentic AI architecture, including planning, memory, and tool use.
• Strong programming proficiency in Python (including PySpark), SQL, and ML frameworks. Hands‑on experience with LLM orchestration frameworks (e.g., LangChain, Semantic Kernel, AutoGen, MS Copilot, etc.).
• Understanding of telco financial structures (ARPU, OPEX / CAPEX, customer lifecycle metrics).
• Knowledge of cloud platforms (Azure preferred)
• Knowledge and experience with MLOps, CI / CD and distributed version control systems (preferred Git).