Senior Data Scientist
2017 - 2020YSANCE- Implemented a Recurrent Neural Network to predict purchases with 95% accuracy.
- Designed and successfully put into production a recommender system for retailers.
- Finalized various proof-of-concept projects to help retailers make use of their data.
Technologies: Pandas, Scrum, Google Cloud Platform (GCP), BigQuery, Jupyter Notebook, SQL, TensorFlow, Keras, PythonData Scientist
2015 - 2015VOODOO- Uncovered general trends for the first mobile game of the company with in-depth, descriptive statistics.
- Developed churn prediction and other mathematical applications to improve mobile games.
- Managed user acquisition on Facebook ads networks and Google Adwords for four mobile apps in over 20 countries.
Technologies: SQL, Matplotlib, Scikit-learn, Python
Benjamin Larrousse
Data Science Developer in Paris, France
Member since July 10, 2020
Benjamin is a talented senior data scientist who earned a Ph.D. in applied mathematics and has a strong focus on optimization and game theory. He uses expert-level analytics skills to deliver data and predictions, enabling clients to make strategic decisions that benefit profits as well as customers. He recently implemented Recurrent Neural Networks to predict purchases with 95% accuracy. Benjamin is passionate about science and loves using mathematics to make the world a better place.
Benjamin is now available for hire
Experience
- Mathematics 8 years
- SQL 6 years
- Python 3 6 years
- Data Science 6 years
- Machine Learning 6 years
- Keras 3 years
- TensorFlow 3 years
- Deep Learning 3 years
Availability
Part-time
Preferred Environment
Google Cloud Platform (GCP), BigQuery, Scikit-learn, SQL, Keras, TensorFlow, Jupyter Notebook, Python
The most amazing...
...Recurrent Neural Network I've implemented used TensorFlow on the Google Cloud Platform to predict the probability of purchases with 95% accuracy.
Employment
Experience
- A Data Perspective: Is it Possible to Defend Against Messi?https://github.com/BenjaminLarrousse/statsbomb-messi
Analysis of the Messi biography dataset helped uncover insights about how to defend against him. Data exploration involved 15 years of data with Python (Plotly for data visualization) and advanced football metrics. Workflow occurred with Jupyter Notebooks, including one for unit testing.
Skills
Languages
Python 3, SQL, PythonParadigms
Data Science, Data-driven Methodology, ScrumOther
Mathematics, Game Theory, Machine Learning, Research, Information Theory, Optimization, Deep Learning, Artificial Intelligence (AI), Algorithms, Football, Sports, AnalyticsLibraries/APIs
TensorFlow, Keras, Scikit-learn, Pandas, MatplotlibTools
TensorBoard, MATLAB, BigQueryPlatforms
Jupyter Notebook, Google Cloud Platform (GCP)
Education
- Ph.D. in Applied Mathematics2011 - 2014Université Paris Sud XI - Paris, France
Certifications
- Introduction to Football AnalyticsAPRIL 2020 - PRESENTStatsBomb
- Deep Learning with TensorFlowMARCH 2017 - PRESENTBig Data University
- Data Science MethodologyJANUARY 2017 - PRESENTBig Data University
- Machine LearningAPRIL 2015 - PRESENTCoursera
