Finnish Center for Astronomy with ESO (FINCA)

• Lead of a research program concerning the injection of energy within clouds in galaxies.
• Detection of weak signal in radio astronomy spectra using mathematical modelling.
• Processing and advanced analysis of infrared hyper-spectral data (8,000 spectra) to detect weak signal.
• Prediction of the relations between galaxies and the central supermassive black hole.
• Parameter fitting of theoretical models of the physical conditions of clouds in galaxies using Bayesian inference.
• Modelling of the multi-wavelength (UV-to-IR) emission of galaxies based on Bayesian inference and curve fitting.
• Compilation of the outputs from theoretical models into a relational database (about a million entries).
• Processing of radio astronomy data from multiple observatories.
• Publication of scientific publications and presentation in international conferences.
• Responsible of the observations with the 14m radio telescope of Metsähovi Radio Observatory (each shift was one week long).
• Comprehensive teaching in two M.Sc. level courses.
• Supervision of two B.Sc. and M.Sc. students.

Postdoctoral Researcher | Data Scientist

INAOE

Remote work due to the COVID-19 pandemic.

• Lead of the analysis of radio astronomy data which was central for the publication of 3 scientific articles (+1 article in preparation)
• Detection of weak signal in radio astronomy spectra using mathematical modelling.
• Modelling of the 3D emission of a galaxy to determine its rotation pattern.
• Modelling of the multi-wavelength (UV-to-IR) emission of galaxies.
• Processing of radio astronomy data from multiple observatories.
• Publication of scientific publications and presentation in international conferences.

Universidad Nacional Autónoma de México (UNAM)

• Detection of weak signal in radio astronomy spectra using mathematical modelling.
• Use of clustering prediction methods to identify clouds in large hyper-spectral radio astronomy images.
• Parameter fitting of theoretical models of the physical conditions of clouds in galaxies using Bayesian inference.
• Processing of radio astronomy data from multiple observatories, handling up to 200 GB at once.
• Publication of scientific publications and presentation in international conferences.
• Comprehensive teaching in two M.Sc. level courses.

Paris-Sud University (Paris XI)

• Detection of weak signal from large and complex hyper-spectral radio astronomy images (more than 500,000 spectra) using mathematical modelling.
• Contributed to the development of ROHSA, an algorithm designed to decompose hyper-spectral observations into a sum of coherent Gaussian. This has been widely utilised in numerous research projects by the astronomical community, resulting in 55 publications stemming from its application.
• Processing of 1.9 million spectra from radio astronomical data to produce hyper-spectral datasets.
• Collection and processing of radio astronomy data from multiple observatories.
• Publication of scientific publications and presentation in international conferences.

Teaching physics at Bachelor level:
• Exercise sessions to see applications of theoretical concepts taught during the lectures.
• Teaching the scientific method during lab experiments.
• "Colleur": examiner for oral exams in physics.

Teaching Assistant

Observatoire de Paris | PSL

Preparation of my PhD thesis at LERMA:
• Detection of weak signal in radio astronomy spectra using mathematical modelling.
• Spatial analysis of optical/infrared astronomical images.
• Prediction of the relation between the presence of gas in galaxies and the formation of stars.
• Collection and processing of radio astronomy data from multiple observatories, handling 60 GB at once.
• Publication of scientific publications and presentation in international conferences.

PHD Candidate | Junior Data Scientist

Research internship as part of my M.Sc. studies:
• Spatial analysis of infrared astronomical images of a diffuse molecular cloud of the Milky Way.
• Identification, characterization and statistical analysis of small clumps.
• Physical modelling of the clumps to determine that the clumps are unlikely to form stars.
• This work results in the publication of a scientific article.

Research Assistant | Junior Data Scientist

University of Helsinki

Research internship as part of my M.Sc. studies:
• Spatial analysis of infrared astronomical images in region of star formation.
• Identification, characterization and statistical analysis of young stellar objects.
• Modelling of the multi-wavelength IR emission from the young stellar objects to derive their mass.

Research internship as part of my B.Sc. studies:
• Time-series analysis of the light curve from ~1000 stars to study their variation.
• Statistical analysis of the insights from the individual light curves.

I am an experienced data scientist (10+ years of experience in academic research), with a strong background in applying machine learning, predictive modeling, and big data analytics of complex, multi-dimensional datasets. Proficient in data processing and problem solving, I also have strong communication skills, both spoken and written.

I am now seeking to transition from a successful academic career to industry.

Skills:
- Programming: Python, LaTeX, GitHub
- Data Analysis: Pandas, Numpy, Scipy, SQL
- Data Visualisation: Matplotlib, Seaborn, PowerBI
- Machine Learning: SciKit-Learn, TensorFlow, PyTorch

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