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La preghiamo di verificare di possedere il livello di esperienza e le qualifiche adeguate leggendo la panoramica completa di questa occasione qui sotto.

- 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

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- 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. xysqume Proficient in mentoring junior data scientists and managing client relationships while translating complex technical concepts for non-technical stakeholders.

Highest-signal resume keywords

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- Machine Learning Expertise

- Python Programming

- Model Validation and Evaluation

- A/B Testing and Causal Inference

- Cloud Provider Experience

Hard Skills

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- Machine Learning

- Applied Analytics

- Model Deployment

- Statistics

- Python

- SQL

- ML/DL Frameworks

- Gradient Boosting Libraries

- Data Validation

- Analytics Engineering

Soft Skills

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- Mentorship

- Client Relationship Management

- Communication

Industry Keywords

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- Data Science

- Digital Advertising

- Marketing Platforms

- MLOps

- Consulting

Tools & Technologies

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- GCP

- Azure

- AWS

- BigQuery

- Snowflake

- Git

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📌 Senior Data Scientist (Piemonte)
🏢 Jobtailor
📍 Piemonte