Senior Data Scientist

The main responsibilities of the position include:

• Lead the design, development, and delivery of high-impact data science and machine learning solutions. 

• Translate complex business challenges into structured analytical approaches and scalable data products. 

• Build, evaluate, and optimize advanced machine learning models, ensuring high standards of quality, performance, and reliability. 

• Contribute to technical decisions and best practices across the data science lifecycle. 

• Review and validate data preparation, feature engineering, model selection, experimentation, and documentation. 

• Support the deployment and operationalization of machine learning models in batch and real-time environments. 

• Present analytical insights and recommendations to technical and non-technical stakeholders. 

• Ensure compliance with data quality, model governance, security, privacy, and responsible AI standards. 

• Identify opportunities to leverage data science for automation, forecasting, personalization, optimization, and risk management. 

• Collaborate closely with Data Engineers, Machine Learning Engineers, Software Engineers, Product Owners, and business stakeholders to develop production-ready solutions. 

• Contribute to improving team processes, technical standards, and project delivery methodologies. 

• Support the Lead Data Scientist in defining priorities, roadmaps, and strategic initiatives. 

Main requirements:

• University degree in Mathematics, Physics, Engineering, Computer Science, Data Science, or a related field. 

• At least 5 years of experience in a similar role. 

• Hands-on experience with Python libraries such as Pandas, NumPy, and Polars for data processing and analysis. 

• Strong Python programming skills with the ability to write clean, maintainable, and production-ready code. 

• Strong knowledge of modern machine learning techniques and advanced architectures, including Transformers and Graph Neural Networks (GNNs). 

• Experience with data visualization libraries such as Matplotlib, Seaborn, and Plotly. 

• Good knowledge of SQL and statistical analysis. 

• Excellent analytical thinking and problem-solving skills. 

• High attention to detail and commitment to delivering high-quality solutions. 

• Strong communication skills with the ability to explain technical concepts to non-technical audiences. 

• Excellent verbal and written communication skills in English. 

• A collaborative mindset, curiosity, and a passion for continuous learning. 

What would be considered as an advantage:

• Exposure to Natural Language Processing (NLP). 

• Experience working with NoSQL databases. 

• Knowledge of software engineering best practices. 

• Experience working in Unix/Linux environments. 

• Basic understanding of AWS services and cloud-based machine learning environments. 

Benefit from:

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