Junior Data Scientist

Who are we?

JS is an IT consulting firm specialized in the Anti Financial Crime transformation.

We act as technical and business partner to our clients, facilitating the translation from “business needs” to tailor-made technical solutions.

Our job is delivering highly qualified consultancy on the ground of your AFC IT infrastructure in order to secure, boost or smoothen your transformation or your business-as-usual activities.

We integrate into our clients’ value chains meeting project needs, supporting resource ramp-up, providing functional or technical expertise that support achieving transformation goals within the expected deadlines or taking on entire end-to-end projects (installation and integration of new solutions, upgrade projects, migration, or massive evolution of existing solutions).

Who are we looking for?

We are seeking a Junior Data Scientist to join a dynamic, AI-focused team dedicated to delivering tangible business value through innovative technologies.

In this role, you will support the development of AI solutions by contributing to data exploration, data preparation, and model development activities, working closely with more senior team members. You will operate in a collaborative and growth-oriented environment, gaining exposure to real-world use cases across sectors such as financial services, insurance, and public administration.

Required Qualifications:

• Master’s degree in a STEM discipline (or equivalent practical experience)
• Foundational understanding of Machine Learning concepts and common AI models
• Basic knowledge of data handling and relational databases
• Good programming fundamentals in Python (or similar languages)

Preferred Qualifications:

• Academic or internship experience in AI/ML projects
• Familiarity with version control systems (e.g., Git)
• Exposure to data visualization tools (e.g., Power BI or similar)
• Interest or initial exposure to AI agent frameworks (e.g., LangChain or similar)

Technical Skills

• Basic to intermediate programming skills in Python
• Familiarity with common data science libraries such as:

Pandas, NumPy

Scikit-learn

• Exposure to deep learning frameworks (e.g., TensorFlow, PyTorch, Keras) is a plus
• Basic knowledge of SQL

Languages:

• Mandatory: English, fluent written and spoken;
• Optional: other European language