19 set - Torino
JobLeads
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La preghiamo di verificare di possedere il livello di esperienza e le qualifiche adeguate leggendo la panoramica completa di questa possibilità 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. xykwogc 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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