We are looking for a Data Scientist with strong knowledge in machine learning, mathematical modeling, and optimization, to develop and improve the intelligent purchasing engine used by our clients. This engine is the core of our platform and automates key business decisions, meaning your work will have a direct impact on user experience and client outcomes.
🧑💻 Work setup: Hybrid – 2 days per week at the office
What are we looking for?
A person passionate about artificial intelligence and applied data science, who enjoys solving complex problems and designing smart solutions. Someone capable of turning mathematical theory into practical, scalable algorithms, with an analytical mindset and a focus on results.
Knowledge of supply chain or procurement is a big plus.
Responsibilities
Design, develop, and validate machine learning models and optimization algorithms to automate purchasing decisions.
Improve the existing AI engine with new ideas, adjustments, or redesigns based on real-world data.
Collaborate with engineering, product, and business teams to translate needs into AI-based solutions.
Experiment with real data in environments like Databricks, applying statistical, ML, and heuristic techniques.
Contribute to the evolution of our AI platform by documenting and sharing learnings.
Your day-to-day will include
Exploratory data analysis and preprocessing.
ML & AI model development.
Experiment design and cross-validation.
Continuous improvement of models in production.
Exploring new methodologies and AI/ML approaches.
Participating in technical and product design sessions.
Tech stack
Languages: Python (required), SQL
Platform: Databricks (including MLflow, Delta Lake, Spark)
Version control: Git
Other (nice to have): Pandas, NumPy, Airflow, Docker, Ray
Requirements
Background in Mathematics, Statistics, Data Science, Engineering, or similar.
Experience designing and validating ML models applied to real-world problems.
Proficiency in Python for analysis and modeling.
Solid understanding of statistics and both supervised and unsupervised learning.
Ability to translate business problems into technical solutions.
Intermediate level of technical English.
Nice to have
Previous experience with mathematical optimization.
Knowledge of MLOps practices (training and deployment in production).
Experience with Big Data or distributed computing environments.
Interest in SaaS platforms or products based on intelligent decision-making.
Strong knowledge in supply chain or procurement is highly valued.
What do we offer? (Beyond salary)
Join a growing technical team, working with real data and complex problems.
A flexible and collaborative environment, with autonomy to propose new ideas.
Projects with real impact on clients and users.
Access to cutting-edge cloud tools (Databricks, MLflow, etc.).
