Nathan - Data Scientist PYTHON

Ref : 200211R002

75018 PARIS
Data Scientist, Data Analyst (30 ans)
Totalement mobile
Mandataire social de sa structure Freelance (SARL, SAS, EURL, etc)

Compétences

PYTHON

SQL

LINUX

VBA

Expériences professionnelles

Professional experiences

CTO and co-fonder at Agence_33_corp Paris, France August 2019 – Currently enrolled
Development of social network tools to increase the impact of an online marketing campaign:
Instagram bot: (Python) Scrapping list of followers, popularity of each of them, mass direct messaging from an account with random time lapse.

Data Scientist at Sia Partners Paris, France March 2019 – July 2019
Traffic modeling (Python): Graph optimization (NetworkX: Dijkstra, A*), flow modeling (BPR model), Reinforcement Learning
Computer Vision Object detection (Python): pool detection using satellite images with YOLO algorithm

Data Science R&D engineer at Neumann AI - Beirut, Lebanon July 2018 – November 2018
Working on the Research and Development team on several projects using:
- Supervised classification and regression algorithms: Tree methods (decision trees, random forest), KNN, Logistic regression, Naive Bayes methods, MLP, etc.
- Ensembles methods; especially gradient boosting (XGBoost)

Consultant at Accenture Consulting Paris, France January 2017 – June 2017
Support in digital transformation and automation of the supply chain in the banking sector, particularly for the Société Générale:
- Project management in the implementation of Big Data, Machine Learning tools and other innovative solutions
- Organizational and functional analysis of the business

Repo Trading at HSBC (end-of-studies internship) - Paris, France January 2016 – August 2016
- Development of tools and strategies of optimization of the IM impact on the swap market (IRS, OIS, CDS…)
- Development of tools in python for the optimization of the collateral management

Mathematics private teacher September 2014 - August 2015
- Private teacher in Mathematics, Statistics and probabilities theory for high school and undergraduate students

Études et formations

Educational Background
Sciences Po Paris September 2017 – January 2019
Master in Public Affairs (MPA): Digital and new technologies specialization - Network economy and Innovation law
- Psychology and public policies
- Econometrics
- Python for Social Sciences

Telecom SudParis September 2013 – September 2016
Engineering degree with a specialization in Machine Learning
- Deep Learning for computer vision (RBM and CNN)
- Supervised and unsupervised learning: decision tree methods, random forest, Naive Bayes Classifier, Regression models, KNN, Gradient boosting
- Biostatistics
- Economic modeling: Applied econometrics for market finance, macro-Economics, time series, research project, social network modelling

Classes Préparatoires aux Grandes Ecoles : MPSI-MP (MathSup-MathSpé) September 2011 – July 2013
Post-secondary highly selective preparatory classes in mathematics, preparing for entrance examinations to the French “Grandes Ecoles”
Additional courses and Academic exchange:

La Trobe University of Melbourne academic exchange: Statistics and applied Mathematics February 2015 – September 2015

Certificates:
- TOEIC: 955/990
- Deep Learning with Python DataCamp
- Convolutional neural network with Python DataCamp
- Stanford Machine Learning MOOC Coursera

Personal projects
Reinforcement Learning: (Python: Gym/Keras) Application of Q-Learning and DQN to different environments. Comparison of hyper-parameters efficiency.
Computer vision: MNIST Kaggl