Job description
Joining our strategic Data Science & AI Team, within the Chief Data & Product Development Office, you’ll have the opportunity to collaborate with key Decision Makers and recognized experts in the Data Science and ML field in a fast-paced, growth-oriented, enthusiastic and customer-focused environment, to strengthen Wind Tre leadership position as AI-powered organization.
We are looking for truly passionate Data Scientists, eager to challenge the business-as-usual and generate an impact at P&L level by applying data-driven methodologies to the business context.
Main responsibilities and activities
Partner with key Decision Makers to explore high-value business opportunities to be translated in data-driven use cases, starting from problem framing and hypothesis testing to the interpretation and actionability of results
Address complex analytics, predictive, simulation and optimization scenarios (multi-variate, heterogeneous sources, large volume, raw data) leveraging on Machine Learning, Artificial Intelligence methodologies and programmatic tools
Manage the end-to-end modeling lifecycle from prototyping to industrialization: discovery, training, testing, serving, monitoring & value tracking, automation
Drive within the Data Science & AI Team the evolution of the Machine Learning automation architecture to spread best practices and increase the operational efficiency
Required Skills
3+ years track of records in Data Science or Machine Learning roles, in major consulting firms or big international companies
Demonstrated experience on applying data-driven methodologies to real world business issues and opportunities
Mastering statistical modeling and modern Machine Learning algorithms (classification, clustering, forecasting, recommendation, reinforcement learning) and model lifecycle management methodologies (CRISP-DM)
Fluent in data wrangling and preparation: exploratory data analysis, profiling & cleansing, feature selection, feature engineering
Professional knowledge on programming languages (Python, SQL), data science libraries (Pandas, Scikit-learn, Gradient Boosting, SHAP), MLOps tools (Git, Airflow, Kubernetes) and advanced data visualization libraries and tools (Matplotlib, Seaborn, Altair, Tableau)
Experience with the Google Cloud ecosystem and Deep Learning frameworks (Keras, TensorFlow, PyTorch) is a plus
Preferred working experience on Telco companies, data science applied to Commercial use cases (segmentation, x-sell & up-sell, churn prediction, fraud prediction, network analysis, …) and AI products (virtual agents, bots, …)
Education
Master's degree or PhD level in a quantitative discipline such as Computer Engineering, Applied Physics / Mathematics, Engineering, Statistics, Econometrics
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