Data Scientist

pAt Ayesa Digital we grow with you
/ppbr/ppEvery 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.
/ppbr/ppAyesa 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.
/ppbr/ppWe 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.
/ppbr/ppThe 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.
/ppbr/ppYou 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.
/ppbr/ppIf 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.
/ppbr/ppWhat You Will Do (Responsibilities) /pulliDesign and implement data-driven solutions using advanced analytics, machine learning, and artificial intelligence techniques.
/liliDevelop predictive and analytical models using technologies such as Python, R, SAS, Spark, Scikit-learn, TensorFlow, PyTorch, or Hugging Face.
/liliApply machine learning and natural language processing techniques to address business and analytical challenges.
/liliDesign and implement data preparation, ETL, and data engineering processes to create high-quality datasets for analytical and machine learning workloads.
/liliDevelop and manage analytical workflows and MLOps processes, including CI/CD pipelines, model registries, testing, reproducibility, and model lifecycle management.
/liliDesign and implement scalable data storage and processing solutions using SQL, NoSQL, MongoDB, Hadoop, data lakes, lakehouses, or distributed data platforms.
/liliDevelop and operationalise machine learning models through APIs, containerisation, model-serving frameworks, and scalable deployment architectures.
/liliDesign and conduct experiments, including A/B testing, cross-validation, significance testing, and other validation techniques, to assess model performance and reliability.
/liliApply advanced analytics techniques to use cases such as forecasting, recommendation systems, anomaly detection, sentiment analysis, and other data-driven applications.
/liliAnalyse model outputs and analytical findings to identify relevant insights, communicate conclusions, and support strategic business decision-making.
/liliContribute to the definition and implementation of AI governance, compliance, risk management, transparency, explainability, fairness, and accountability practices.
/liliSupport the monitoring and mitigation of AI and machine learning risks, including bias, model drift, data quality issues, and other model-related risks.
/liliEnsure that data science and AI solutions are designed in accordance with applicable data protection, AI, legal, and ethical requirements.
/liliCollaborate with technical and business stakeholders to translate complex analytical results into clear and actionable recommendations.
/li /ulpbr/ppWhat We Are Looking For (Requirements) /pulliAdvanced professional experience as a Data Scientist, Machine Learning Engineer, AI Specialist, Advanced Analytics Consultant, or similar role.
/liliStrong professional experience with advanced analytics and data science using Python, R, SAS, Spark, or comparable technologies.
/liliStrong experience with machine learning and artificial intelligence frameworks such as Scikit-learn, TensorFlow, PyTorch, Hugging Face, or comparable technologies.
/liliSolid experience with programming and data manipulation using Python, R, SQL, or comparable languages.
/liliProfessional experience with data engineering and ETL processes using technologies such as Talend, Informatica, dbt, Azure Data Factory, or equivalent tools.
/liliExperience