Data Scientist / Python Developer
Role details
Job location
Tech stack
Job description
We are seeking a talented and motivated Data Scientist & Python Developer to join our growing team in Madrid. Your primary focus will be to develop models and tools to identify financial instrument data quality issues and make clean up recommendations. By joining our team, you will have the opportunity to design and create a solution from scratch and support the team with existing solutions & models. Moreover, you will be encouraged to propose your own modeling ideas, directly contributing to our transformative goals.
YOUR CHALLENGE
- Lead end-to-end development of data-driven models, from exploratory analysis and feature engineering to modelling, validation, deployment, monitoring, and comprehensive documentation
- Design, build, and optimise robust data pipelines to ensure high-quality, reliable, and timely access to structured and semi-structured financial datasets
- Develop and enhance solutions for identifying and resolving financial data anomalies, including prototyping novel algorithms and improving existing methodologies
- Define and implement meaningful performance metrics and impact assessments to evaluate model effectiveness against clear business objectives
- Support the migration and integration of current models into a new enterprise-grade data science platform, ensuring scalability, reproducibility, and compliance
- Create intuitive, interactive dashboards (e.g., via Tableau or similar tools) to visualise insights and facilitate stakeholder engagement
- Collaborate actively in agile, multidisciplinary teams - championing best practices, peer review, knowledge sharing, and continuous improvement
Requirements
Master's degree in Data Science, Statistics, Mathematics, Physics, Computer Science, or a related quantitative field (completed or in the process of completing)
- Excellent analytical and problem-solving skills with strong attention to detail
- Sound theoretical understanding of core probability and statistics concepts, along with familiarity with popular machine learning methods (experience with recommendation systems is a plus)
- Proven proficiency in Python for data analysis and automation (libraries such as pandas, scikit-learn, NumPy, PyTorch/TensorFlow); solid command of SQL for querying large-scale databases
- Familiarity with software engineering and DevOps principles, particularly around code versioning (Git), testing, CI/CD pipelines, and containerisation (Docker, Kubernetes) is highly valued
- Hands-on experience in extracting, transforming, organizing, and interpreting data
- Basic understanding of financial markets and products
- Good verbal and written communication skills, with an ability to convey complex and technical topics to non-technical stakeholders
- Comfortable working in a dynamic and fast-paced environment, showcasing a high level of autonomy
- Proactive, curious, creative, and eager to learn
- Fluent in English, Spanish is a plus