Über Juan Manuel
Spanisch
Muttersprachlich oder zweisprachig
Englisch
Konversationssicher
Projekt- und Berufserfahrung
- Cobee-Pluxee,Product Data ScientistMärz 2024 - April 2025 (1 Jahr und 1 Monat)Madrid, Spain• Led the redesign and implementation of a scalable billing system, replacing legacy Tableau processes and increasing operational efficiency. . Migrated key business dashboards to Metabase, im-proving accessibility, performance, and visibility into strategic KPIs. . Designed and deployed multiple ETL pipelines using DBT and Clickhouse to support core analytics and product initiatives.• Collaborated with product and engineering teams to translate business needs into data-driven solutions.• Development of prototyping and idea validation with generative Al
- LadorianMachine Learning EngineerFebruar 2022 - März 2024 (2 Jahre und 1 Monat)Madrid, Spanien. Refactored and optimized the company's ML codebase in Python, improving performance and scalability; migrated applicable logic to BigQuery SQL for improved data efficiency.• Developed models to correlate sales with weather data and perform cross-analyses of sociodemographic segments. . Built a sales forecasting model integrated into the Google Cloud Platform ecosystem, powering real-time decision-making.
- IESE Business SchoolTeaching assistant, Python for Data AnalysisJanuar 2022 - Dezember 2022 (11 Monate)Barcelona, Spanien. Guided participants in learning programming fundamentals, data manipulation, and visualization using Pandas, NumPy, and Matplotlib.
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Ausbildung und Abschlüsse
- Data ScienceThe bridge. Digital talent2021Programming: Python (IDEs: PyCharm, VisualStudio, Jupyter) - Version control: Git - Databases: SQL - Data Sources: APIs, Web Scrapping (Selenium, BeautifulSoup) - EDA, Analysing data, data cleaning, data mining: Pandas, Numpy, SQL, Spark - Data visualization: Matplotlib, Seaborn, Pandas, Plotly - Dashboarding: Power BI - Machine Learning: Supervised & Unsupervised Learning: Scikit-Learn (Linear Regression, Polynomial Regression, Logistic Regression, PCA, SVM, KNN, Tree-Based Models and Ensembles, Clustering algorithms…, Machine Learning with PySpark and Databricks) - Deep Learning: TensorFlow, Keras (Deep Neural Networks, Convolutional Neural Networks, Transfer Learning, Embeddings) - Natural Language Processing: NLTK, SpaCy, Textacy (Stemming, lemmatization, vectorization, tokenization, Sentiment Analysis) - Big Data & ETL: Spark, Databricks, PySpark, AWS Cloud - Model deployment: Flask, Heroku, AWS
- Inteligencia ArtificialMadrid 42 fundación TelefónicaVisualmente, la metodología se compone de siete círculos concéntricos, que representan al Common Core, a los que se añaden multitud de satélites a su alrededor que corresponden a las especializaciones. Dentro del Common Core se aprenden nociones fundamentales de programación con proyectos de formación básica. Dentro de mi especialización , estoy centrado en Bid Data e Inteligencia Artificial