Data Scientist

Altia; Madrid; Presencial; EUR 45.000 - 75.000; Jornada completa

Descripción de la vacante

Altia is seeking a Data Scientist to join its European team, working on international projects for a significant European Agency. The role requires strong analytics, ML/NLP expertise, and proficiency in Python, R, and SQL. You will collaborate with UX and product teams to design, implement and monitor data-driven solutions.

Join a team that emphasizes reproducibility, scalable data pipelines, and robust analytics architectures, with opportunities to shape advanced analytics across projects.

Formación

• Knowledge of advanced analytics techniques and tools (Python, R, SAS, Spark) to design and implement data-driven solutions.
• Knowledge of machine learning and NLP (scikit-learn, TensorFlow, PyTorch, Hugging Face) to build predictive and text-based models.
• Knowledge of programming languages (Python, R, SQL; Perl optional) used in data science for modelling and automation.
• Knowledge of MLOps practices (CI/CD pipelines, model registry, unit testing) to ensure reproducibility and quality in model delivery.
• Knowledge of BI tools (Tableau, SAS, SAP Analytics) to visualise and communicate model outputs and insights.
• Knowledge of data engineering and ETL processes using tools (Talend, Informatica, dbt, Azure Data Factory) to prepare training datasets.
• Knowledge of data storage and query technologies (SQL, NoSQL, MongoDB, Hadoop) to extract and process data at scale.
• High level of English.

Responsabilidades

• 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 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.

Conocimientos

Frame business problems

Present models clearly

Accuracy and reproducibility

Design and test approaches

Manage experiments and pipelines

Explore new algorithms and AI methods

Interpret analytical findings

English proficiency

Herramientas

Python

R

SQL

Perl (optional)

Scikit-learn

TensorFlow

PyTorch

Hugging Face

Tableau

SAP Analytics

Talend

Informatica

dbt

Azure Data Factory

NoSQL

MongoDB

Hadoop

Descripción del empleo

Do you want to start a new professional challenge? Check out our new opportunity! We are looking to incorporate a Data Scientist to our team.

About us

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

Our project and team

This is your opportunity to start working on international projects with a highly qualified team and applying the latest technologies. You will join our European team, specifically the one involved in several projects for a significant European Agency.

Minimum Requirements

Required Knowledge

• 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.

Main Responsibilities

• 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.

Skills:

• 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.

This job offer has been drafted with impartiality and non-discrimination on the basis of gender, race, ideology or any other grounds in mind. In particular, it complies with current regulations on gender equality between women and men (Royal Decree-Law 6/2019)