09/28/2026 updated
100 % available
Senior Data Scientist | R & Shiny Expert
Alcorcon, Spain
Only remote
MSc in Data ScienceData AnalysisData IntegrationR (Programming Language)Machine LearningRStudioSmart DataBusiness Intelligence Development StudioData ScienceAWS Data AnalyticsReactive ProgrammingSynthesizing DataDatabricks
R & Shiny Development
Expertise in reactive programming and the development of production-grade interactive dashboards using R and Shiny, including asynchronous computation (promises/future) for responsive, data-heavy applications and full deployment workflows.
Machine Learning & Statistical Computing
Proficiency in designing and implementing Machine Learning pipelines in Python and R, covering XGBoost, clustering, dimensionality reduction, regression, ensemble methods, cross-validation, A/B testing, time series analysis, forecasting, and confidence interval estimation.
Deep Learning & Generative AI
Hands-on experience with TensorFlow, Keras, Bayesian optimization, multi-target prediction, text embeddings (GloVe), and integration of generative AI tools including LLMs and Claude Code to accelerate model development and code generation.
Programming Languages
Strong programming background in R, Python, and SQL, applied across data analysis, model development, and automation tasks.
Data Integration & Automation
Experience with BigQuery, dbt, Airflow, Git, CI/CD pipelines, Google Cloud Platform, and internal library development to build robust end-to-end analytics pipelines.
Data Visualization & Reporting
Skilled in creating insightful visualizations and reports using Shiny, Tableau, Power BI, Plotly, and Microsoft Office tools to communicate findings to C-level stakeholders and business teams.
Demographic Inference & Segmentation
Design and implementation of demographic inference models and segmentation approaches combining clustering and dimensionality reduction techniques for large-scale audience measurement systems.
Business Intelligence
Development of predictive models and automated dashboards using Tableau and Microsoft Office tools, with experience translating data insights into strategic business decisions.
Expertise in reactive programming and the development of production-grade interactive dashboards using R and Shiny, including asynchronous computation (promises/future) for responsive, data-heavy applications and full deployment workflows.
Machine Learning & Statistical Computing
Proficiency in designing and implementing Machine Learning pipelines in Python and R, covering XGBoost, clustering, dimensionality reduction, regression, ensemble methods, cross-validation, A/B testing, time series analysis, forecasting, and confidence interval estimation.
Deep Learning & Generative AI
Hands-on experience with TensorFlow, Keras, Bayesian optimization, multi-target prediction, text embeddings (GloVe), and integration of generative AI tools including LLMs and Claude Code to accelerate model development and code generation.
Programming Languages
Strong programming background in R, Python, and SQL, applied across data analysis, model development, and automation tasks.
Data Integration & Automation
Experience with BigQuery, dbt, Airflow, Git, CI/CD pipelines, Google Cloud Platform, and internal library development to build robust end-to-end analytics pipelines.
Data Visualization & Reporting
Skilled in creating insightful visualizations and reports using Shiny, Tableau, Power BI, Plotly, and Microsoft Office tools to communicate findings to C-level stakeholders and business teams.
Demographic Inference & Segmentation
Design and implementation of demographic inference models and segmentation approaches combining clustering and dimensionality reduction techniques for large-scale audience measurement systems.
Business Intelligence
Development of predictive models and automated dashboards using Tableau and Microsoft Office tools, with experience translating data insights into strategic business decisions.
Experience
Professional experience5 - 10 years
Freelancer since2026
Languages
EnglishFluentSpanishNative speaker
Project history
Developed model Teletest 2.0, the official TV audience measurement system based on approximately 1.1M devices, serving as the industry currency in a 1.5B advertising market. Significantly improved system quality, reducing zero audience occurrences by approximately 95% and advertising reach variability by approximately 85%. Designed and implemented Machine Learning pipelines (Python, R) in production, including demographic inference models (XGBoost), segmentation, and Deep Learning (TensorFlow, Keras) for real-time prediction. Integrated generative AI tools (LLMs) to accelerate model development and code generation. Delivered insights through interactive R Shiny dashboards to C-level stakeholders and TV network executives, and mentored Junior Data Scientists.
Performed large-scale data analysis to identify patterns, trends, and anomalies, generating actionable insights that supported predictive modeling. Collaborated closely with engineering, product, and business teams to translate data insights into strategic decisions.
Built Machine Learning and experimentation pipelines. Developed interactive R Shiny dashboards and advanced data visualizations, applying asynchronous computation (promises/future) for responsive, data-heavy pages.