Ă€ propos de Lucas
Français
Bilingue ou natif
Anglais
Capacité professionnelle complète
Espagnol
Capacité professionnelle limitée
Expériences
- ACCORData & analytics engineerHÔTELLERIEjanvier 2024 - mai 2024 (5 mois)Support dans la migration combinée des données d'Accor (entrepôt de données et source analytics) en tant que freelance à temps plein.❖ Migration de l'entrepôt de données GCP vers Snowflake.❖ Migration de la source de données GA3 vers GA4 et des flux associés (outil interne).❖ Intégration de la source dans les couches de transformation existantes.❖ Sessionization des événements et reconstruction des segments de séquence avec contrainte de volume de données élevé.❖ Modélisation des tables de faits et de dimensions pour mettre à jour les tableaux de bord.❖ Création de datamarts pour mettre à jour les tableaux de bord (Tableau).❖ Création de datamarts pour alimenter les scénarios d'activation via reverse ETL (Hightouch).
- M13H | Data Marketing & technology consultingSenior Data engineer & analytics engineerCONSEIL & AUDITjuillet 2022 - août 2023 (1 an et 1 mois)Paris, FranceAs a Consultant - Data science & analytics engineer at M13h, I design and implement data pipelines, integrate data from various sources, and build data infrastructure for high-performance data analytics.We use technologies such as Python, SQL, and Cloud (GCP / AWS) to deliver value to our clients through data-driven insights and solutions.Implementation of Customer Data Platform (CDP) on different cloud environments (GCP, AWS & Azure). Creation and industrialization of different micro-services:❖ ETL for ingesting raw data sources (transactions, CRM, web, products...) within a data warehouse❖ Transformation of raw data via a SQL workflow using the DBT framework❖ Realization of different marketing use cases (modeling, reporting, activation)
- ELEVATE | Agence Data & Technologies MarketingSenior Data Consultant (Marketing, Engineering & Science)CONSEIL & AUDITjanvier 2020 - juin 2023 (3 ans et 6 mois)Paris, FranceDATA COLLECTIONâť– Auditing on Google Analytics, and TMS (Google Tag Manager & Tag Commander ... ) to ensure reliable data exploitation and collection.âť– Tool setup and configurations: Google Analytics, Google BigQuery, AT Internet, Google Data Studio, Tag Commander & Google Tag Manager)âť– Redaction of tracking plans to expand the range of data collected. DATA ENGINEERING & SCIENCEâť– Data pipeline development: Designing, implementing, and optimizing data pipelines.âť– Data modeling: Modeling data for data science projects, using techniques such as regression, factor analysis, and machine learning.âť– Data analysis: Analyzing data for companies in various industries, using analysis techniques such as descriptive analysis, exploratory analysis, and survival analysis.DATA ANALYSIS & ACTIVATIONâť– Data Visualization: through Google Data Studio, Looker, Reeport and automated tablesâť– Conversion Rate Optimization (CRO): A/B Testing, tracking and optimization of conversion's funnelsâť– Performance measurement: definition of relevant KPI. (campaigns, audience, user's behavior)CONSULTING & MANAGEMENTâť– Project management : Definition of goals, planning, expressing and understanding needs.âť– Ressource management : Identification of needs and attribution of human ressourcesâť– Internal & external ressources training & upskillingâť– Commercial Offer and Sales: Developing and structuring commercial offers for consulting services, and participating in sales processes by preparing presentations and commercial proposals.
Avis
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Formations
- LEAD - data science & engineeringJedha Bootcamp2023Formation aux notions de pointe du data-engineering (120 heures) âť– Deployment & distributed ML : Docker, Kubernetes, Ray âť– Reinforcement learning : Rlib, Gym OpenAI âť– Data Pipelines : Airbyte, Kafka, Neo4J âť– Automation & Workflows : Airflow, Zapier + Projet data-science
- FULLSTACK - Concepteur en science des donnéesJedha Bootcamp2022Formation aux notions avancées de la data science (500 heures): ❖ Exploratory data analysis : Data Manipulation, Statistics and Seaborn, Distributions and Matplotlib, Interactive Graphs ❖ Data Collection and Management: Web Scrapping, Data Storage on AWS & GCP, ETL Processes ❖ Big Data : Distributed Computing with Spark SQL, PySpark & DataBricks ❖ Supervised ML : Pre-Processing, Linear regressions, Regularization and Hyperparameter Optimization, Logistic Regression, Decision Trees and Random Forest, SVM, Ensemble Learning, Model Selection and Evaluation, Time Series ❖ Unsupervised ML : KMeans, DBSCAN, Dimensionality Reduction, Natural Language Processing NLP, Topic Modeling ❖ Deep Learning : Gradient Descent, Introduction to neural networks, Introduction to tensorflow, Convolutional Neural Network, Transfer Learning, GAN, Word Embedding, Text Classification, Encoder Decoder ❖ Deployment : Docker, Dashboarding with Dash, MLFlow, Conda, Flask, SageMaker + Projet data-science
Certifications
- dbt FundamentalsDBT2023
- Certification Commander ActCommanders Act2020