Senior Data Scientist @ hubQuest

What we expect 5+ years of professional experience in Data Science or ML Engineering, including production deployments MSc or PhD in Computer Science, Statistics, Mathematics, Physics, or related technical field Strong Python programming skills, including software engineering practices (OOP, modular code design, testing) Solid experience with ML frameworks and NumFOCUS stack: pandas, scikit-learn, SciPy, Matplotlib, NumPy Hands-on experience with PySpark and large-scale data processing Familiarity with Azure cloud ecosystem (Databricks, ML Studio, Data Factory, Azure DevOps) Understanding of CI/CD and MLOps pipelines, containerization (Docker, Kubernetes), and model deployment Experience designing robust validation and monitoring strategies for ML models in production Strong analytical mindset, excellent problem-solving skills, and the ability to think critically about model behavior Fluency in English (spoken and written), as you’ll collaborate globally Nice to have Experience with Infrastructure as Code (Terraform) Familiarity with DBT for data transformation Knowledge of deep learning frameworks (TensorFlow, PyTorch) Experience working in agile, cross-functional environments Exposure to multi-tenant or global-scale data systems We are a team of tech and data enthusiasts on a mission to bring together the best minds in IT and analytics. Our goal? To build cutting-edge analytical hubs that empower our partners to become truly data-driven organizations. We are currently looking for a Senior Data Scientist to lead the design, development, and deployment of advanced analytical solutions within the Global Analytics Unit — a centralized, global team driving smart data products across all business areas. This is a high-impact role for someone who thrives on end-to-end ownership: from exploratory data analysis and model design, through refactoring and stability testing, to production deployment and performance monitoring. Why join us If you’re looking for an opportunity to: Tackle complex, real-world business challenges using advanced analytics and machine learning Build and deploy production-grade models that shape decisions across global markets Work with an exceptional international team of Data Scientists, ML Engineers, and Data Engineers Influence architectural and methodological decisions in a rapidly growing global analytics organization Operate in an environment that values autonomy, innovation, and technical excellence …this might be the perfect fit for you. You’ll also enjoy: Flexible working hours and remote/hybrid work model Private medical care and Multisport card Access to online learning platforms, certifications, and global knowledge exchange A relaxed, non-corporate atmosphere with genuine respect for expertise and ownership A modern office in central Warsaw with great transport links As a Senior Data Scientist, you will take ownership of developing and productionizing advanced data science models and services. Your work will go far beyond notebooks — you’ll help design stable, reproducible, and automated ML pipelines. In short We’re looking for a Senior Data Scientist who’s not just great at modeling — but who writes clean, production-ready Python, builds pipelines that last, and obsesses over model robustness, automation, and stability. You’ll join a team where experimentation meets engineering — and where your models will directly shape global business decisions. ,[Lead end-to-end data science projects, from problem framing and data exploration to deployment and monitoring, Develop, refactor, and productionize robust data preprocessing pipelines for increased stability and scalability, Build and maintain reusable helper functions for hyperparameter optimization, feature selection, and model evaluation, Improve model accuracy and diagnostics using weighted R², adjusted R², Xi correlation, RMSE, and MAE metrics, Design and implement comprehensive model stability testing frameworks, including:, Automate baseline validation and implement standardized approaches to benchmark model performance, Work closely with Data Engineers and MLOps Specialists to deploy models into production using Azure-based infrastructure, Refactor and optimize data pipelines and REST services to ensure scalability and low-latency performance, Collaborate with business stakeholders to translate analytical insights into actionable recommendations] Requirements: Data science, Machine learning, Python, PySpark, Statistics, Azure, Databricks, MLOps, Terraform, dbt, Deep learning Tools: Jira, Agile, Scrum. Additionally: Sport subscription, Private healthcare, Training budget, Small teams, International projects, Free coffee, Bike parking, Free beverages, In-house trainings, In-house hack days, Modern office, No dress code.