- Design, develop and validate solutions across classical machine learning, applied AI, agents, copilots, LLM-based services and advanced statistics - Bring solutions to production with the appropriate level of rigor - Select methods including experimentation, A/B testing, backtesting and causal inference to prove business impact - Own 2-3 client projects end-to-end in parallel - Manage relationships with senior client stakeholders - Identify recurring patterns across projects and abstract them into reusable frameworks and accelerators with the CTO - Mentor junior data scientists - Contribute to the team's training roadmap - Support Client Managers in pre-sales scoping - Translate business requirements into technical architectures and realistic estimates - Bring solutions to production in collaboration with Data Engineering and Analytics Engineering colleagues - Translate technical work into clear narratives for non-technical stakeholders Requirements - Fluent Italian, C1 English - 8+ years of experience in data science, machine learning or applied analytics - At least 2 years in a senior capacity with technical ownership of projects and mentorship of junior colleagues - Strong Python (pandas, NumPy) - ML/DL frameworks: scikit-learn, PyTorch, TensorFlow - Gradient boosting libraries: XGBoost, LightGBM, CatBoost - Solid foundations in statistics, probability and ML theory - Proven experience with model validation and evaluation, avoiding overfitting and data leakage - Experience with A/B testing, backtesting and causal inference techniques - At least one shipped LLM use case (RAG, agent,



copilot or similar - Advanced SQL - Familiarity with data warehouses such as BigQuery or Snowflake - Hands-on experience with at least one cloud provider: GCP, Azure or AWS - Experience with model deployment, monitoring and logging in production - Git and collaborative development - Clean, testable and maintainable code beyond notebooks - Track record of models shipped to production with measurable business impact - Analytics engineering experience with digital advertising and marketing platform data is a plus - Experience turning one-off solutions into reusable internal tools, frameworks or products is a plus - MLOps practices such as CI/CD for models, feature stores and orchestration are a plus - Experience in consulting or product companies with a strong data science practice is a plus - Experience working with international stakeholders is a plus Core Competencies Demonstrates expertise in machine learning, applied AI, and advanced statistics, with a strong focus on model validation, deployment, and business impact. Proficient in mentoring junior data scientists and managing client relationships while translating complex technical concepts for non-technical stakeholders. Highest-signal resume keywords - Machine Learning Expertise - Python Programming - Model Validation and Evaluation - A/B Testing and Causal Inference - Cloud Provider Experience Hard Skills - Machine Learning - Applied Analytics - Model Deployment - Statistics - Python - SQL - ML/DL Frameworks - Gradient Boosting Libraries - Data Validation - Analytics Engineering Soft Skills - Mentorship - Client Relationship Management - Communication Industry Keywords - Data Science - Digital Advertising - Marketing Platforms - MLOps - Consulting Tools & Technologies - GCP - Azure - AWS - BigQuery - Snowflake - Git

📌 Senior Data Scientist (Verbania)
🏢 Jobtailor
📍 Verbania