À propos de Pierre
Data Scientist for almost 2 years, I am fascinated by cutting-edge technology and CRISPR Genome Engineering particularly.
I have experience carrying out Machine Learning projects from their early conception, through data engineering, model building and optimization, all the way to production. I previously worked with CROs, pharmaceutical laboratories and biomedical research centers (Excelya, Bristol Myers Squibb, Harvard Medical School, etc), but I am open and curious to discover other sectors.
My technical expertise revolves around the Python stack (Jupyter, Scikit-learn, Tensorflow, Pandas, Seaborn, etc.), I am also proficient in R, SQL and I am comfortable working on UNIX systems and within the Agile methodology.
Furthermore, I am a great communicator and I really enjoy teaching and vulgarizing Data Science to a non-technical audience.
Anglais
Bilingue ou natif
Français
Bilingue ou natif
Espagnol
Capacité professionnelle limitée
Accepte de travailler sur site
Paris (jusqu’à 10 km)
Expériences
- EXCELYAData ScientistINDUSTRIE PHARMACEUTIQUEnovembre 2019 - Aujourd'hui (6 ans et 7 mois)Paris Area, France➤ Data Science consulting for Bristol Myers Squibb on a machine learning classification project predicting patients’ retention to a specific drug➤ Exploration and processing of clinicaltrials.org database with NLP techniques and advanced analysis of textual data➤ Development and teaching of an in-depth Python training program➤ Creation of a Data Science problematics catalogue for clients and sales lead➤ Set up of Data Science trainings for collaborators
- Harvard Medical SchoolBioinformatics Data ScientistCENTRES DE RECHERCHEmars 2018 - août 2018 (6 mois)Greater Boston Area6 months Master's internship in the Perrimon Lab at Harvard Medical School, Genetics Department.Subject : ⇒ Machine Learning predictions of CRISPR/Cas9 on-target efficiency in Drosophila melanogaster.In this project my aim was to provide the Drosophila RNAi Screening Center (DRSC) with an accurate CRISPR sgRNA efficiency scoring tool in order to improve the sgRNA design pipeline. I used Machine Learning algorithms to model the efficiency of sgRNAs targeting essential genes, based on their characteristics, in a D.mel genome-wide pooled CRISPR screen. The Machine Learning models identified were implemented in a command-line tool with which single or batch sgRNA efficiency predictions can be made from the raw sgRNA sequence (see GitHub link).Skills :➤ Programming and Machine Learning in Python and R➤ CRISPR/Cas9 genetic engineering, molecular genetics and genomics➤ Scientific literature review, autonomy, public speaking, GitHub version control
- Pierre and Marie Curie UniversityBioinformatics Data ScientistCENTRES DE RECHERCHEjuillet 2017 - août 2017 (1 mois)Paris Area, FranceTwo months internship in the Laboratory of Theoretical Physics and Condensed Matter. (LPTMC - UMR CNRS 7600)Subject : ⇒ Expressed genes domain identification of different cell types by high-throughput data analysis.I helped in the development of a machine learning pipeline to infer the best preprocessing method to detect expression signals in complex datasets. The datasets' cell types are then to be clusterized into large cellular groups (brain, blood, gut, etc...) according to their presumed expression pattern (unsupervised machine learning).Skills :➤ Python programming (Jupyter, NumPy, Pandas, Scikit-Learn, Matplotlib etc...)➤ Handling very large datasets (over 250Gb of RAM)➤ Data cleaning, visualization and processing (.bed/.hdf5, large arrays, sparse matrix etc...)
Recommandations
Soyez le premier à recommander Pierre
Contribuez à la réussite de ce freelance en partageant votre expérience de collaboration avec lui.
Ces profils de freelance correspondent également à vos critères
Agatha Frydrych
Backend Java Software Engineer
4.7
(3)
2
Baptiste Duhen
Fullstack developer
4.6
(4)
5
Amed Hamou
Senior Lead Developer
4
(2)
7
Audrey Champion
Web developer
4.3
(3)
4
Formations
- Master's degreeParis-Sud University (Paris XI)2018Paris-Sud University is one of the largest and most renowned French university, particularly in science and mathematics. ▷ The University ranked 41 in the Academic Ranking of World Universities 2017. As an active participant in scientific research (2 Nobel prizes, 4 Fields medals, 2400 researchers), Paris-Sud University is involved in disseminating scientific knowledge and has a long-standing tradition of international openness towards foreign universities and research centers. International exchange at Paris-Sud accounts for : ▹ 5,000 foreign students from 144 countries ▹ 315 ERASMUS exchanges ▹ 150 new joint PhDs per year Main courses : ▹ Programming (Python, Java, PHP, C, Perl) and software engineering ▹ Databases optimization (SQL) ▹ Comparative genomics and statistical analysis of genomes ▹ Biostatistics + Machine Learning with R ▹ NGS + Big Data ▹ Processing and analysis of biological images ▹ Structural biology ▹ Analysis of dynamic systems + biological simulation
- Bachelor's degreeUniversité de Versailles Saint-Quentin-en-Yvelines2015UVSQ is the leading university in France in terms of student success at the bachelor level and ranks third for the number of apprentices in the Île-de-France, reflecting a strategy that prioritizes educational innovation and professionally-focused international programs. UVSQ actively cultivates projects with high potential for knowledge and technology transfer with industry partners in strategic sectors of the French economy. With partner institutions around the world, UVSQ students, faculty, and staff have the opportunity to go abroad while UVSQ welcomes their counterparts in France. International programs in the UVSQ account for : ▹ 150 bilateral agreements ▹ 120 partner universities (Lifelong Learning Program) ▹ 80 cooperation agreements with universities throughout the world Main courses : ▹ Cell Biology ▹ Genetics and Genomics ▹ Biostatistics ▹ Population Genetics/Genomics ▹ Immunology, Virology & Parasitology ▹ Physiology & Chemistry