Data Scientist Ii (Remote) - Special Client Project
Pubblicato il 17-10-2026 - AGILE LAB in Milano
**Agile Lab** is a company founded in 2014 with the mission to create value for its customers in data-intensive environments through customisable solutions that establish performance-driven processes, sustainable architectures and automated platforms based on data governance best practices. Having delivered over 100 successful Elite Data Engineering initiatives, we have used this experience to create Witboost: a modular, technology-agnostic platform that enables modern organisations to discover, value and produce their data in both traditional environments and fully compliant Data Mesh architectures. With a highly skilled team of over 260 data engineers based in Europe, Agile Lab helps organisations with their data-driven transformation. Take a look at our **handbook** to discover our core values and processes. **The Opportunity**:
We are looking for a skilled** Data Scientist II to join a unique project in partnership with a primary industry client.** **This role follows a specific “Train & Hire” path**: - **Phase 1 (First 6 months)**: You will work as a consultant focused on this specific project, undergoing specialized on-the-job training to master the client’s domain and technology stack.
- **Phase 2 (Hire)**: Upon successful completion of the 6-month period, **you will be directly hired by the client**, with a **guaranteed salary increase.** For this role, you should have in-depth knowledge of statistics and classical machine learning. Experience with time series analysis is required. Familiarity with MLOps practices and collaborative software development workflows is considered a plus. **RAL: €38.5K - €48.5K** **Responsibilities**: - **Analyzes business requirements**and determines a suitable solution autonomously, **evaluating if an ML-based solution is feasible;**: - Good understanding of business requirements;
- **Develops and fine-tunes models through reproducible experiments;**:
- **Builds ML solutions** incorporating software engineering quality standards **(SDLC)**and **data engineering best practices;**: - Participates in the **technical design of features with guidance;**: - Understands and optimizes and monitors model performances;
- Prioritizes tasks with autonomy based on requirements and proper context. **️ Requirements**: - Bachelor's degree in Computer Engineering or Computer Science;
- Previous experience as a Data Scientist or Machine Learning Engineer **(+2 years)**;
- **In-depth knowledge of at least one machine learning framework** such as **Tensorflow, PyTorch or scikit-learn;**: - Experience with timeseries analysis is required;
- **Good Knowledge of programming languages** including advanced **Python patterns**;
- Familiarity with **software lifecycle practices** (testing, release, deploy) and git-based workflows;
- **Knowledge of MLOps practices**;
- **Ability to explain ML results and limitations to tech and non-technical audiences;**: - Good project management skills;
- Good communication skill;
- Languages: both Italian and English;
- Team Player. **We offer**: - Career Accelerator: A structured 6-month path leading to direct employment with a top-tier client and a salary step-up;
- Remote or lavoro da remoto and work life balance;
- Training monthly budget;
- Benefits and corporate welfare programs: meal vouchers, health fund provided, prizes, welcome pack with all the equipment you need to work;
- Agile Nomads experience: opportunity to work for 2 weeks abroad;
- The opportunity to attend one conference per year;
- Inclusive environment where you can be who you really are;
- Stimulating environment oriented to growth, both professional and personal. **How we work**: - We don't like hierarchies: we work as a team;
- We don't like bureaucracies; we prefer sense of responsibility;
- We like data, certainly, so anything that is measurable;
- We want to make a positive change in our industry;
- Empathy, humility, collaboration, and willingness to challenge ourselves are the basis of our work. Please note: