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Piotr ŁĄCZKOWSKI

PARIS

En résumé

Young, dynamic and passionate R&D Engineer/Data Scientist with strong ability to cope with complex problems and concepts. Quick learner with a solid scientific background, experienced in high responsibility innovative international projects.
Interested in Artificial Intelligence and Machine Learning R&D, BigData, software development, Data-Mining, fast-growing start-ups. A good team player with a sense of humour, rigorous and result oriented, communicative, eager to knowledge sharing and exchange.

Mes compétences :
Nanotechnologies
E-beam lithographie
Semiconducteurs
Python
Spintronics
Data analyses and automatization
Simulation numérique
Metal Spintronics
R&D
Documentation
Algorithmie
Debuging
Business Analytics
Statistique appliquée
Développement web
Leadership
Gestion de projet
Deep Learning
Management
Agile Scrum
Docker
E-commerce
Data Mining
Spark
Dask
Big Data
Gestion d'équipe
Data Science
Machine Learning
Tensorflow
Sklearn
Github
AWS
AngularJS
HTML
Django

Entreprises

  • BackMarket - Head of Data (Machine Learning and Big Data)/Full Stack Django, Python at BackMarket

    2016 - maintenant Head of Machine Learning and Artificial Intelligence development for business intelligence (Supervised, Unsupervised Learning and Deep Learning, predictions, chatbot, translations systems, recommendation systems). Data visualization and modelling, advanced algorithm engineering for e-commerce platforms. Code development and optimisation, advanced interactive visualizations and reporting.
    Technology: Django, Python 2, Python 3, Angularjs, HTML, jquery, git, gitlab, jira, AWS, S3 + all data science kit ( tensorflow, Keras, sklearn, numpy, pandas, scipy, mpl, Seaborn), Tableau, Alteryx, Vertica, MySQL, Snoflake, Snowplow, Docker, Linux, PySpark...

  • Unite Mixte CNRS/Thales - Post-Doc R&D Engineer

    2012 - 2016 Worked in an international team of scientists led by a Nobel Prize winner: Albert Fert.

    Signal and Data acquisition (Labview, Matlab, Python, GPIB, MPL, GUI Design), Data Analysis, processing and modeling (ML - classification algorithms, FEM, parallel cluster calculations). nanodevices and nanofabrication (transistors, memristors, skyrmions and domain wall tracks, bio-inspired computing). Data visualization, project management.

  • CEA/INAC/SP2M/NM - PhD Student

    2009 - 2012 Spintronics and Nanofabrication. Data acquisition, analysis, modelling and visualisation (Python, FEM, parallel computing, PyQT-GUI), advanced algorithms development. Regression, fitting, classification, gradient descent and grid search.

  • Institut Néel - CNRS - Intern

    2007 - 2008 Construction and calibration of the low noise scanning Hall probe microscope for the study of hard NiFeB nano-magnets, MEMS.

  • Institu Neel - CNRS - Intern

    2006 - 2006 Study of magnetic vortexes in non-conventional superconducting materials (heavy fermions) using a u-SQUID scanning probe microscope mounted on a dilution cryostat.

Formations

Pas de formation renseignée

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