Data Scientist

• Collaborate with stakeholders to collect requirements, frame business problems as data science hypotheses, define success metrics, and develop or deploy advanced data mining and machine learning solutions.
• Collaborate with User Experience (UX) and product teams to specify design requirements for the effective presentation and interpretation of model outputs and insights.
• Develop process to monitor and analyse data accuracy
• Identify, collect, and prepare data for analysis, collaborating with Data Analysts to ensure robust production-grade data pipelines, with a focus on feature engineering and data readiness for modelling.
• Produce data models according to specific problems statements.
• Develop and implement machine learning algorithms, statistical models, and scripts to solve specific business problems.
• Collaborate with Data Analysts and Architects on the design of the analytics architecture to ensure it supports the scalability and performance requirements of data science models.
• Write the different documentation associated with the tasks and liaise with other teams as necessary to address cross-system interdependencies.

• Knowledge of advanced analytics techniques and tools (e.g., Python, R, SAS, Spark) to design and implement data-driven solutions.
• Knowledge of machine learning and natural language processing (e.g., Scikit-learn, TensorFlow, PyTorch, Hugging Face) to build predictive and text-based models.
• Knowledge of programming languages (e.g., Python, R, SQL; Perl optional) commonly used in data science for modelling and automation.
• Knowledge of MLOps practices (e.g., CI/CD pipelines, model registry, unit testing frameworks) to ensure reproducibility and quality in model delivery.
• Knowledge of business intelligence tools (e.g., Tableau, SAS, SAP Analytics) to visualise and communicate model outputs and insights.
• Knowledge of data engineering and ETL processes using tools (e.g., Talend, Informatica, dbt, Azure Data Factory) to prepare training datasets.
• Knowledge of data storage and query technologies (e.g., SQL, NoSQL, MongoDB, Hadoop) to extract and process data at scale.
• High level of English., * Ability to frame business problems, form hypotheses, and design solutions.
• Skill in presenting models and insights clearly to all audiences.
• Commitment to accuracy, reproducibility, and integrity in models.
• Ability to design and test approaches for complex challenges.
• Competence in managing experiments, pipelines, and deliverables.
• Drive to explore new algorithms, frameworks, and AI methods.
• Ability to interpret analytical findings to tell a compelling story that clearly prescribes business actions and drives strategic decision-making.
• Ability to understand, speak and write English, optionally French as an additional asset.

We are an IT Consultant Group that provides services and creates digital solutions to improve the lives of citizens across Europe. Check out our website: www.altia.es/en