Looking for a job

Fernando Davó Miralles

@fernandodavmiralles

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I build production data systems, predictive models, and LLM tooling for large-scale analysis.

Spain

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What I'm looking for

I’m looking to apply my production data-science experience and chemistry/physics background to computational biology, bioinformatics, or large-scale scientific data problems.

At Gauss & Neumann, I build search and performance data systems at scale for international advertisers. I use Python and SQL to develop pipelines, predictive and optimisation models, experimental design, causal impact analysis, and Bayesian inference.

Since June 2024, I’ve led a small data team through work allocation, code review, mentoring, and reproducibility conventions. I also build LLM-based internal tooling using embeddings, retrieval, and agent workflows to automate multi-step analysis.

My chemistry and physics training gave me hands-on computational research experience, from protein–metalloligand docking at InSiliChem to angiogenic morphogenesis modelling at CRM. I’ve also worked with detector and gamma-ray data through IFAE, CERN, and PIC computing facilities.

I’m currently completing an MSc in Bioinformatics and Biostatistics, applying R and Python to computational genomics, omics analysis, statistical inference, and regression modelling. I bring wet-adjacent chemistry knowledge together with production engineering discipline over large datasets.

Experience

Work history, roles, and key accomplishments

Current

Data Scientist

Current

Gauss & Neumann

Jan 2020 - Present (6 years 8 months)

Lead a small data team, building predictive and optimisation models, causal impact analysis, and Bayesian inference at production scale. Developed LLM-based internal tooling for semantic grouping, retrieval, and agent workflows.

Undergraduate Researcher

Centre de Recerca Matemàtica (CRM)

Jan 2020 - Dec 2020 (11 months)

Developed mathematical and computational models of angiogenic morphogenesis, including numerical simulation and statistical validation against biological data.

Mathematical Modelling Numerical Simulation Statistical Validation

Undergraduate Researcher

InSiliChem Group, UAB

Jan 2020 - Dec 2020 (11 months)

Implemented novel computational approaches for protein–metalloligand interaction, optimised docking simulations, and analysed large-scale molecular datasets.

Molecular Docking Protein Ligand Interaction Molecular Dataset Analysis Computational Chemistry

Research Student

IFAE - Institute for High Energy Physics

Jan 2018 - Dec 2019 (1 year 11 months)

Characterised silicon detectors using TCT and test-beam campaigns at CERN, and integrated MAGIC gamma-ray data into a big data platform at PIC computing facilities.

Device Characterization TCT Test Beam Big Data Data Integration

Research Student

Universitat Politècnica de Catalunya

Jan 2017 - Dec 2018 (1 year 11 months)

Performed data analysis and laboratory work for neutron detector development.

Data Analysis Laboratory Work Neutron Detectors

Summer Researcher

Universitat d'Alacant

Jan 2017 - Dec 2017 (11 months)

Conducted structural measurement of planar molecules by scanning tunnelling microscopy.

Scanning Tunneling Microscopy Structural Measurements

Education

Degrees, certifications, and relevant coursework

Universitat Oberta de Catalunya & Universitat de Barcelona

MSc, Bioinformatics and Biostatistics

2026 -

Official 60-ECTS master's degree in Bioinformatics and Biostatistics, taught in R and Python, covering structural and molecular biology, computational genomics, omics data analysis, statistical inference, and regression modelling.