I help aspiring Data Scientist & Machine Learning Engineer to achieve their goals !
My main goal is to developp the best AI-system for Dog's Activity Recognition. Our purpose is not just to have the best AI-system but to propose the best smart collar for dogs on the market !
In parallel I am developing the research and development part in order to explore other deep learning approaches. To succes theses tasks I am working with a Machine Learning Engineer who is supporting me on the project related to the data.
In addition to the implementation of the machine learning project end-to-end, I am working on the setting up of tools to improve the project management, the data visualisation and the workflow of our data. All of the tools implemented are open source.
I focused on the implementation of a recommender system (Products approach), Association Rules, scoring (of interest) and segmentations with the objective of developing the CRM.
I have implemented the time series forecasting with RNN with the aim of predicting the activity at the call center to scale the teams. I have also contributed to the implementation of a Proof Of Concept about the speech to text based on the algorithm WaveNet (DeepMind). I was able to use NLP’s algorithms in order to explore and to do an analysis of the surveys data.
About the tech I use: Pyspark, Hive, Dataiku,Tensorflow and Python
Mentoring of students on the Central Supelec Data Scientist Course. Through projects about Machine Learning , DeepLearning, Recommander System and technological survey.
I help aspiring Data Scientist & Machine Learning Engineer to achieve their goal !
Training in Machine Learning - 2019 - In Progress...
Consulting Data Scientist - Jagger & Lewis
May 2018 - August 2018
- Set up Machine Learning & Deep Learning models to improve the quality of the solution
Mentor Data Scientist - Self Employed
May 2018 - June 2018
Trainer at Quantmetry, Data Science Consulting
3 training days about the Machine Learning with Python and Big Data with Pyspark:
- Algorithm of Machine Learning (Classification - Regression - Clustering)
- Use cases (Risk Prediction)
- Good practices (Exploratory Data Analysis)
- Hadoop - Spark - Churn Prediction with Pyspark (MLlib)
Data Scientist at Pitchr
March 2017 – November 2017
Implementation of an recommender system - Collaborative Filtering Approach - to sort smarter the people around the Pitchr's users. The goal was to sort a list of people caracterized by theirs professional skills in order to increase the number of connections between the users.
COFIDIS - CRM Analytics (January 2016 à December 2017)
- Implementation of the Data Management Platform
CREDIT AGRICOLE NDF - CRM Analytics (January 2015-January 2016)
- Data Muggling with the platform Cloudera (Hive, Spark...)
- Implementation of ML's algorithm
- Reporting to monitor the activity
- Production of KPI to pilot the activity
- Setting up the calculation of bonuses for employees
- Implementation of Reactivation's score
- Monitoring of Key account
- Rewriting SPSS programs in SAS