Curriculum vitae

Summary

With over 15 years of experience in computational biology, drug discovery, and data science, I specialize in utilizing advanced computational methodologies to drive innovation in biological research. My expertise spans high-performance computing, molecular simulations, and biophysics, enabling me to decode complex biological systems and accelerate drug discovery efforts. Additionally, I excel in deploying big data applications and leveraging machine learning techniques to extract valuable insights from large datasets.

Education

• B.Sc. Molecular Biology, Universitat de Girona, 2003
• M.Sc. Bioinformatics and Computational Biology, Universidad Complutense de Madrid, 2004
• Ph.D. in Physical Chemistry, Universidad de Granada, 2012

Experience

Senior ML Engineer II @ Recursion Pharmaceuticals

(Toronto, CANADA | August 2025 – Present)

• Advanced Data Processing & Orchestration: Drove the data ingestion and standardization process for a large-scale ML platform.
• Applied agentic solutions to streamline workflows and automate complex decision-making processes, significantly reducing toil in drug discovery.

Senior Data Scientist @ Recursion Pharmaceuticals

(Toronto, CANADA | April 2023 – July 2025)

• Automated Hit-to-Lead Pipeline: Built a comprehensive, automated platform to guide compound selection through multiple decision stages.
• Developed predictive models for cytotoxicity and potency, providing crucial insights for compound selection.

Computational Scientist @ Cyclica

(Toronto, CANADA | April 2020 – April 2023)

• Developed an advanced pipeline for high-throughput screening, leveraging ML models to predict drug-target interactions.
• Created a compound generation engine using Enamine’s synthetic chemistry building blocks.

Postdoctoral Fellow @ University of Toronto

(Toronto, CANADA | April 2014 – April 2020)

• Designed pipelines for biological data collection from heterogeneous sources.
• Implemented deep learning models for cancer classification using multi-omics data.
• Mentored undergraduate and graduate students.

PhD Student, Research Assistant @ University of Granada

(Granada, SPAIN | September 2007 – December 2013)

• Conducted novel analysis of allosteric effects on proteins using large-scale simulations.
• Developed automated pipelines for analyzing water molecules in peptide recognition domains.

Scientific Data Manager @ Almirall Pharma

(Barcelona, SPAIN | January 2005 – August 2007)

• Designed and implemented protocols for preprocessing and digital storage of experimental data.

Volunteer and Internships

• Scientific Consultant @ Meta (formerly Sciencescape), 2014
• Master Student @ GRIB-IMIM, 2003–2004
• Research Assistant Intern @ Hospital Universitari de Tarragona Joan XXIII, 2002
• Lab Assistant Intern @ Bioberica Pharma, 2001

Courses & Certificates

Languages

• Spanish: Native
• Catalan: Native
• English: Professional working proficiency

Core Skills

Programming & Data Science:

• Python (Deeply proficient)
• SQL
• Foundamental data scientist packages: Pandas, NumPy, matplotlib, seaborn, Scikit-Learn, XGBoost

Machine Learning & MLOps:

• ML Model Architecture & Implementation
• Model Selection & Benchmarking
• Data Ingestion, Standardization, Data Preprocessing & Feature Engineering
• ML Lifecycle Management
• Predictive Modeling (e.g., Cytotoxicity, Potency)

Workflow Orchestration & Cloud:

• Prefect
• Docker
• Anyscale
• Continuous Integration/Continuous Deployment
• Git
• GCP

Specialized & Domain Expertise:

• Drug Discovery
• Cheminformatics
• Bioinformatics
• Computational Structural Biology
• Systems Biology
• Molecular Dynamics
• High-Throughput Screening
• Computational Strutural Biology

Soft Skills

• Communication of Complex Technical Concepts
• Cross-functional Collaboration
• Problem-Solving oriented
• Data-decision driven beliver
• Strategic Planning for R&D
• Mentorship & Technical Leadership