Freelancer profile translated to English.
Back to original languageAbout Rodrigue
Graduated from Ecole Polytechnique, Senior Data Scientist, I am available full-time for freelance missions.
I have expertise in all stages of a Data Science project, including:
- Scoping and clarifying needs with business stakeholders
- Data retrieval and exploration
- Data visualization & data cleaning
- Building the data pipeline
- Model training & hyperparameter selection
- Monitoring (Choice of technical & business metrics)
- Model deployment
- Documentation, communication & continuous improvement loop
Furthermore, I also have extensive knowledge in the cryptocurrency ecosystem and macroeconomics. Instagram -> @christ_fund
Attentive to your needs, I will do everything possible to make your Data Science project a success. Do not hesitate to contact me for more information.
English
Fluent
French
Native or bilingual
Spanish
Fluent
Remote only
Primarily works remotely
Experience
- OrangeSenior Data ScientistTELECOMMUNICATIONSDecember 2017 - December 2022 (5 years)Paris, France1. Time series Forecasting 🔭• Forecasting model for customer service advisor availability. 🙋🏽♂️• Deployment on Dataiku Automation Node (scenario creation, Backtesting, drift, model maintenance) ⚙️• Monitoring of tests on the deployed UI and usage by business teams 🕹• Project documentation and development standards writing. 📑
Languages/tools used: Dataiku, Hive, PySpark, Python&R, Keras, Shell... 🧑🏽💻
2. Omnichannel 🖥 <->🏫<->📞• Construction of a foundation for analyzing omnichannel customer journeys 👩🏼🦰👱🏼♂️👴🏽👦🏻• Study of the reiteration of multichannel customersLanguages/tools used: Dataiku, Hive, Spark
3. Complaints 😡🤯• Creation of a steering tool for monitoring performance (DeltaSat/NPS) and root causes of customer dissatisfaction. 😤• Quantification of reasons 📉• Automatic classification of complaints• Implementation of levers to improve customer satisfaction• Monitoring the application of levers in the fieldLanguages/tools used: Dataiku, QLIK/PowerBI, Python&R, Hive
4. Surveys 📧• Construction of a data foundation to feed flash surveys ⚡️Languages/tools used: Dataiku, Hive, Pig, Spark
5. Customer Profiling 🕵🏽• Customer segmentation model in-store | digital 👨🏼🎤🧑🏼💼🧑🏽🔬• Design thinking workshop / Brainstorming 🧠• Creation of a system to improve cross-selling 💶🛍Languages/tools used: Dataiku, Hive, Python&R, QLIK, Agile Mode
6. Automatic Text Processing 🔎📑• Model for detecting root causes of customer dissatisfaction (NLP) 🤬• Corpus preparation (Tokenization, Lemmatization, Stop Word, NER, POS...) 🛀• Topic Modeling (LDA/LSI/Corex algorithm)• Semantic analysis (Word embedding)• Predictive model of customer sentiment and opinion on the Orange customer experienceLanguages/tools used: Dataiku, Gensim, Spacy, TextHero, Python&R, Keras, ML, DL, Transformer.
7. Data Foundation 🏢• Construction of a data cockpit to feed a customer project ⛽️• Searching for tables in the Hub 🔎• Creation of the schema on Dataiku• Definition of indicator calculation rules• Maintenance of the system's data feed• Creation of alerting and crisis scenarios# Languages/tools used: Dataiku, Hadoop, Teradata, Hive, Python&R - Groupe AdeccoData AnalystHUMAN RESOURCESSeptember 2017 - February 2018 (6 months)Lille, France1. HR Data Analysis for Quality Indicator Monitoring• Weekly monitoring of absenteeism rate 📉• Absenteeism profiling 🕵🏽• Mapping of accidents on industrial sites2. Creation of a steering tool on Excel & R in full autonomy• Data flow management•Writing of an explanatory notice for employees•Realization of the tool's architecture and prototype
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Education
- Data Science ProgramEcole Polytechnique Palaiseau2022Avec l’explosion et la profusion des données disponibles dans un grand nombre de domaines, les nouvelles techniques de collecte et d’analyse vont affecter de façon profonde l’ensemble des secteurs de la vie économique, mais aussi certains secteurs de la recherche. La formation offre une introduction aux meilleurs outils méthodologiques pour appréhender et exploiter les données et notamment les données massives (Big Data). Une véritable immersion dans l’univers de la donnée à travers un parcours intensif portant sur les fondamentaux en sciences des données.
- Engineer in Applied Mathematics and Data ScienceEcole Polytechnique de Lyon2019