The candidate will work in the R&D Innovation Department, as part of the Data Science & ML team with other experts in the field and will report to the BI & Data Science Lead.
The main activities required to the selected candidate aims at consolidating and widening the general knowledge and technological knowhow of RGI in the field of the Artificial Intelligence / Machine Learning applications and Predictive Analytics.
Responsibilities
1. Work closely with data scientists, engineers and various stakeholders to grasp the project's goals and develop a clear understanding of machine learning objectives;
2. Develop and optimize LLM-based applications;
3. Develop and implement advanced machine learning algorithms for predictive modeling, with a particular emphasis on statistical learning algorithms;
4. Carrying out activities related to data extraction, cleaning, manipulation, validation, storage, and processing;
5. Collaborate with cross-functional teams, document findings, and ensure compliance with industry regulations;
6. Model Deployment, Model Management and Data Drift Monitoring
Experiences
At least 1 – 2 years’ experience in a Data Scientist role.
Technical Skills
7. Proficiency in the Python programming language and extensive use of its ecosystem, including: Data manipulation and analysis: Pandas, Polars, NumPy Machine Learning: scikit-learn, XGBoost, TensorFlow/PyTorch/Keras, Visualization: Matplotlib, Seaborn, Plotly Statistical Analysis: Statsmodels, SciPy Version control: Git, GitHub
8. Experience with LLM libraries (LiteLLM, LlamaIndex,…)
9. Experience LLM workflows: Embeddings, RAG, fine-tuning,….
10. Proficiency in complex querying construction (SQL) and knowledge of database normalization and data modeling concepts
11. Familiarity with cloud-based platform, such as AWS, and with model deployment as a REST service using FastAPI:
12. Fluent knowledge of English and Italian.
Nice to Have / Plus :
13. Knowledge in ETL tools (.: AirFlow, ….) and management of databases is a plus
14. Experience with R and related packages (.: Shiny…)
15. Use Docker to package the FastAPI application along with its dependencies for easy deployment
16. Leverage Pydantic's data validation capabilities to ensure incoming requests adhere to expected formats
17. Front End prototyping libraries (: Streamlit, Gradio, ….)
18. Proficiency in French/German/Spanish is considered a plus
Personal Characteristics:
19. Analytical Thinker
20. Strong team spirit and an open, cooperative culture, promoting a positive team environment
21. Attention to detail, passion for processes, systems and data mining
22. Willingness of learning and delivering innovation-based products to a wider audience
23. Effective Communicator
24. Results-Driven
25. Ethical and Compliant
Education
Bachelor’s or Master’s Degree in a quantitative field (Physics, Maths, Stats, Computer Science or Computer Engineering, Economics) or equivalent experience.