Anna Estany Macià
Data Scientist with hands-on experience developing machine-learning solutions, automated data workflows and validation pipelines for real-world industrial data. Experienced in Python, SQL, time-series analysis, feature engineering, model development and data quality, with a strong focus on reproducible and scalable analytical workflows. At NIRA Dynamics, developed an automated anomaly-detection pipeline covering 10+ automotive signals and benchmarked multiple ML/DL approaches, achieving case-level F1 scores of up to ~0.87. Strong interest in ML engineering, MLOps and cloud-based AI solutions, with hands-on experience in AWS and a multidisciplinary background in Data Science and Applied Physics.
Work History
Master Thesis Student - Automotive Data Analytics
5 MonthsProject: Anomaly Detection in Automotive Sensor Data Using Machine Learning
- End-to-End ML Development: Developed an automated anomaly-detection pipeline covering 10+ automotive signals, from data preprocessing and feature engineering to model evaluation, validation and reporting.
- Model Development: Benchmarked 4 machine-learning and deep-learning approaches—LOF, Isolation Forest, One-Class SVM and LSTM Autoencoder—achieving case-level F1 scores of up to ~0.87.
- Workflow Automation: Built reusable Python and MATLAB workflows for data cleaning, preprocessing, feature extraction, model testing and validation, replacing a multi-step manual process.
- Data Quality: Worked with real-world automotive time-series data, identifying anomalous behavior and ensuring reliable data for downstream algorithm development.
Specialist Technician and Researcher
2 Years- End-to-End Research: Led projects from experimental design and data collection to analysis and validation.
- Data Analysis: Processed and interpreted data from multiple measurement systems.
- Technical Communication: Presented results at 8 national and international conferences and co-authored 1 peer-reviewed publication.
Administrative Assistant
1 Year 4 Months- Data Accuracy: Collected, organized and validated customer and administrative data, ensuring accurate and consistent records.
- Reporting: Used advanced Excel functions to prepare reports and identify inconsistencies requiring corrective action.
Programmer Intern
1 Year- Databases: Queried cloud and local databases using SQL to retrieve, structure and prepare data.
- Data Solutions: Developed interactive dashboards and reporting functionality for desktop and mobile applications.
- Testing & Troubleshooting: Supported data processing, software testing and troubleshooting across multiple application environments.
Software Developer Intern
2 Months- Process Automation: Developed a fully automated remote software deployment pipeline for 70+ clients, eliminating the need for on-site software update visits.
- Scripting & Engineering: Developed SQL and PowerShell scripts to automate recurring software and system tasks.
- Software Reliability: Supported debugging, testing, configuration and technical documentation for deployed solutions.
Education
Master of Science - Data Science
Machine Learning & Deep Learning · Statistical Modelling · SQL/NoSQL Databases · Data Pipelines · Big Data Analytics with Hadoop, Spark and Kafka · Cloud Computing through AWS Academy projects · Data Visualization & BI
Master of Science - Nanoscience And Nanotechnology
Sensor systems, measurement techniques, experimental data acquisition, materials characterization and quantitative data analysis.
Bachelor of Science - Applied Physics
Mathematics, modelling, statistics, signal analysis, experimental methods and analytical problem-solving.
Skills
Languages
Publications
Estany-Macià, A., Fort-Grandas, I., Joshi, N., Svendsen, W. E., Dimaki, M., Romano-Rodríguez, A., & Moreno-Sereno, M. (2024). ZIF-8-Based Surface Plasmon Resonance and Fabry–Pérot Sensors for Volatile Organic Compounds. Sensors, 24(13), 4381.
DOI: https://doi.org/10.3390/s24134381