Freelancer profile translated to English.
Back to original languageAbout Eric
With a scientific background, I expanded my skills by completing:
– the Data Analyst training with Openclassrooms in 1 year (10 professional projects with simulations in various companies). The courses offered are in partnership with ENSAE -ENSAI and Centrale Supélec.
– the "Become a Data Analyst" track from LinkedIn Learning in 3 months.
My professional projects (see portfolio and LinkedIn profile) were carried out using Python or SQL, and I worked with:
– for graphical representations: with Seaborn, Matplotlib, Plotly, Tableau, PowerBI, Knime
– for statistical analyses: with Scikitlearn and Stasmodel + Anova, student's t-test, Chi2, linear correlation…
– for script writing: with Jupyter Notebook, IBM database2
– for unsupervised data processing: Principal Component Analysis, K-means, Hierarchical Ascending Classification…
With diplomas and certifications obtained, I wish to offer my data analysis skills to clients in the Île-de-France region with partial or total remote work in the health, environment, technology, energy, transport, real estate, retail, and banking sectors, but I remain open.
I enjoy anything that requires rigor, analysis, and also performing service missions.
My soft skills: conscientious – persevering – analytical mind – versatile – empathetic.
DIY, IT (video editing, photo retouching, data recovery, antivirus installation, Office suite, browser configuration…) occupy my free time, among other things.
French
Native or bilingual
English
Fluent
Can work on-site
Évry-Courcouronnes (up to 15km)
Experience
- "CAPDATA" - Projet pour la formationDetect counterfeit banknotesSOFTWARE PUBLISHINGJanuary 2022 - February 2022 (2 months)Viry-Châtillon, FranceI am a Data Analyst consultant at a company specializing in data. My company has secured a contract for on-site services within the National Organization for the Fight Against Counterfeiting (ONCFM).This institution aims to implement methods for identifying counterfeit euro banknotes.Expected outcomes:- Perform predictive analysis- Perform automatic classifications to partition data (Confusion Matrix, K-means, PCA, Model performance tests)- Perform logistic regression- Perform linear regression
- "DWFA" - Projet pour la formationStudy on drinking water with TableauHEALTH AND WELLNESSOctober 2021 - November 2021 (2 months)Viry-Châtillon, FranceI am a Data Analyst consultant on a mission at the NGO DWFA (Drinking Water For All); its ambition is to provide access to drinking water for everyone.In this context, I am tasked with creating a Dashboard presenting a global view of access to drinking water worldwide. This will allow the selection of a target country once the funder has responded regarding the area of expertise they wish to finance.Expected outcomes:- Generate graphs suitable for data types- Summarize results for a client- Analyze client needs to formulate analytical questions- Create dashboards and a story answering analytical questions
- "Lapage" - Projet pour la formationAnalyze bookstore sales with PythonENTERTAINMENT AND LEISUREAugust 2021 - September 2021 (2 months)Viry-Châtillon, FranceI am a Data Analyst consultant at Lapage, a renowned large online general bookstore. I report directly to the Marketing department.I am involved because the company wants to take stock after two years of operation and analyze its strengths, weaknesses, customer behavior, etc.Expected outcomes:- Perform bivariate analysis to interpret data- Perform statistical tests (Anova, Chi-squared, Pearson)- Analyze time series
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Education
- Data AnalystOpenclassrooms, ENSAE-ENSAI Centrale Supélec2022Analyses de 10 projets professionnalisants détaillés sur mon profil LinkedIn : - Créer et utiliser une base de données immobilière avec SQL - Créer le schéma d'une base de données. - Effectuer des requêtes SQL pour répondre à une problématique métier. - Mettre à jour un catalogue de données (Power BI). - Créer des tables dans une base de données (IBMdatabase2). - Réaliser une étude de santé publique au sein de la FAO (aide aux pays en sous-nutrition) - Utiliser des Librairies (Numpy, Pandas)spécialisées pour les traitements data. - Créer un environnement de développement (Jupyter Notebook) et manipuler des DataFrames en Python . - Réaliser des dashboards. - Analyser les ventes, les points forts/faibles et les comportements clients d'une librairie - Réaliser une analyse bivariée et interpréter des données issues des tableaux de bord (Matplotlib, Seaborn). - Réaliser des Tests statistiques (Anova, Khi-2, Pearson). - Analyser des séries temporelles. - Produire une étude de marché (entreprise agroalimentaire s'ouvrant à l'international) Explorer, gérer les erreurs/incohérences présentes sur des données stockées pour synthétiser des variables. - Effectuer un clustering simple (Classification Ascendante Hiérarchique, K-means)+ACP.
- Certification "Become a Data Analyst"LinkedinLearning2022Analyse approffondie de données et data-visualisation (Tableau, PowerBI, Excel, Statistiques...)