Design, develop, train, and evaluate machine learning and statistical models across a wide range of business challenges.
Explore, analyse, and visualize complex datasets to uncover patterns that matter.
Perform feature engineering, data preprocessing, and selection to maximize model performance.
Design and implement solutions leveraging Large Language Models, Retrieval-Augmented Generation (RAG), and NLP techniques.
Apply image processing, object detection, and visual reasoning techniques to solve problems at scale.
Define and execute robust experimentation frameworks, select appropriate metrics, and validate model performance.
Collaborate with clients across Western Europe and the USA to understand their business challenges and communicate findings clearly.
Keep up with the latest in AI/ML research, emerging techniques, and new tools.
Share your knowledge with junior team members through mentorship and hands-on guidance.

Strong programming skills in Python (e.g. scikit-learn, TensorFlow, PyTorch, pandas, NumPy, Hugging Face, LangChain).
The ability to write clean, maintainable, and reproducible code is essential.
Demonstrated hands-on experience building, training, and evaluating ML models.
Strong understanding of supervised and unsupervised learning techniques, model selection, hyperparameter tuning, and cross-validation.
Understanding of core statistical concepts, probability, and linear algebra.
Experience applying statistical inference, hypothesis testing, or mathematical optimization in practical settings is a plus.
Experience with natural language processing, text analytics, large language models, prompt engineering, RAG architectures, or other GenAI techniques.
Experience with image processing, object detection, visual reasoning, or satellite imagery analysis is an advantage.
Comfortable working with large, messy, real-world datasets.
Proficiency in SQL and experience with data wrangling, cleaning, and transformation.
Experience with cloud platforms (preferably Azure: Databricks, Azure ML, Synapse) or similar services on AWS/GCP.
Familiarity with MLOps practices (model versioning, CI/CD for ML, experiment tracking) is an advantage.
At least 2–3 years of professional experience in data science, machine learning, applied research, or similar analytical roles.
English at B2 level or higher.

Financial Rewards: Benefit from regular salary reviews, performance bonuses and other special bonuses.
Enjoy meal contributions and a cafeteria benefit system offering personalized choices.
Flexibility & Work-Life Balance: Enjoy our hybrid working policy, flexible working hours, 2 extra days off during Christmas along with Sick-days.
Every minute of your extra work is valued and compensated.
Career Development: Engage in tailored internal and external training programs as well as structured career development plan.
Health & Well-being: Access premium benefits such as Multisport card or a medical center membership.
Take advantage of our Well-being and Work-Life Coaching program.
Supportive Culture: Participate in team building activities and social events and join our employee referral program.
Experience a culture with regular feedback and a supportive environment.
Global Opportunities: Seize the opportunity for international assignments and work on diverse projects with international clients.
Explore the world while working with the possibility of working from abroad.
Extra perks: Use various discounts at partner companies such as cars, health care, beauty, culture or others.
Transfer up to 4 telephone numbers at discounted rates.

Data Scientist

Key skills