Data Scientist

At Ayesa Digital we grow with you

Every professional in our company is vital to us. Thanks to their talent, we continue to expand; today, we are a global team of over 11,000 people working toward a common goal.

Ayesa Digital is currently participating in high-impact European Union projects designed to address major European challenges and drive innovation and digital transformation. These are strategic technological projects based on collaborative initiatives that stand out for their international focus and strong commitment to socially-oriented results.

We are currently looking for a Data Scientist / AI & Advanced Analytics professional to join an international project supporting the design and implementation of data-driven, machine learning, and artificial intelligence solutions within a European Union environment.

The role will focus on advanced analytics, machine learning, artificial intelligence, data science, and the development of scalable and reliable analytical solutions. You will combine technical expertise in data science and AI with an understanding of business needs, data engineering, model deployment, governance, and regulatory requirements.

You will work in an international and multicultural environment, collaborating with data engineers, developers, business stakeholders, technical specialists, and other project stakeholders to design analytical solutions, develop and validate models, ensure data and model quality, and support the continuous evolution and operationalisation of AI and advanced analytics capabilities.

If you are an experienced Data Scientist, Machine Learning Engineer, AI Specialist, Advanced Analytics Consultant, or similar professional with a strong background in Python, machine learning, data engineering, MLOps, AI governance, and advanced analytics, this is your place.

What You Will Do (Responsibilities)

• Design and implement data-driven solutions using advanced analytics, machine learning, and artificial intelligence techniques.
• Develop predictive and analytical models using technologies such as Python, R, SAS, Spark, Scikit-learn, TensorFlow, PyTorch, or Hugging Face.
• Apply machine learning and natural language processing techniques to address business and analytical challenges.
• Design and implement data preparation, ETL, and data engineering processes to create high-quality datasets for analytical and machine learning workloads.
• Develop and manage analytical workflows and MLOps processes, including CI/CD pipelines, model registries, testing, reproducibility, and model lifecycle management.
• Design and implement scalable data storage and processing solutions using SQL, NoSQL, MongoDB, Hadoop, data lakes, lakehouses, or distributed data platforms.
• Develop and operationalise machine learning models through APIs, containerisation, model-serving frameworks, and scalable deployment architectures.
• Design and conduct experiments, including A/B testing, cross-validation, significance testing, and other validation techniques, to assess model performance and reliability.
• Apply advanced analytics techniques to use cases such as forecasting, recommendation systems, anomaly detection, sentiment analysis, and other data-driven applications.
• Analyse model outputs and analytical findings to identify relevant insights, communicate conclusions, and support strategic business decision-making.
• Contribute to the definition and implementation of AI governance, compliance, risk management, transparency, explainability, fairness, and accountability practices.
• Support the monitoring and mitigation of AI and machine learning risks, including bias, model drift, data quality issues, and other model-related risks.
• Ensure that data science and AI solutions are designed in accordance with applicable data protection, AI, legal, and ethical requirements.
• Collaborate with technical and business stakeholders to translate complex analytical results into clear and actionable recommendations.

What We Are Looking For (Requirements)

• Advanced professional experience as a Data Scientist, Machine Learning Engineer, AI Specialist, Advanced Analytics Consultant, or similar role.
• Strong professional experience with advanced analytics and data science using Python, R, SAS, Spark, or comparable technologies.
• Strong experience with machine learning and artificial intelligence frameworks such as Scikit-learn, TensorFlow, PyTorch, Hugging Face, or comparable technologies.
• Solid experience with programming and data manipulation using Python, R, SQL, or comparable languages.
• Professional experience with data engineering and ETL processes using technologies such as Talend, Informatica, dbt, Azure Data Factory, or equivalent too