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, Num Py) ML/DL frameworks: scikit-learn, Py Torch, Tensor Flow Gradient boosting libraries: XGBoost, Light GBM, Cat Boost 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 Big Query 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 Big Query Snowflake Git

📌 Senior Data Scientist (Italia)
🏢 Jobtailor
📍 Italia