As a Machine Learning & Data Engineer with 6 years of experience, my work consists of designing and implementing data-driven solutions to help companies leverage the power of their data.
Practical information:
Age : 28 years
Nationality : French
Residency Status : B Permit holder
Years of experience : 6 years
Highest academic degree : Master Of Science in Information Technology
Within the Datalab team of the Strategy & Development department, I worked on several Data & ML projects. Work ranges from proof of concept (PoC) to building data pipelines and deployment in production. Following are a few examples of missions I worked on.
Mission 1: Recommender System. Implementation of a recommender system that suggests companies with high default risk. The algorithm is based on criteria of similarity with the companies already reviewed by the risk underwriters. Tools: Python (pandas, sklearn, pySoT), Gitlab, optimization, Surrogate Modeling, Gower Distance
Mission 2: Complementary insurance. Automating of product profitability reporting, analyzing customer behavior and segmentation, predictive analysis of price sensitivity. Tools: Python (pandas, sklearn, airflow), Gitlab, Airflow, Docker
Mission 3: Balance sheet forecast following the Covid crisis. Modeling the impact of the Covid crisis on company balance sheets in order to adapt the Risk underwriting strategy. Tools: Python (pandas, pymongo), Gitlab
Mission 4: REST API for an external client. Design and implementation of REST API for a customer in the banking sector that allows them to search and identify a company, buy default risk scores and payment behavior insights. Tools: Python (Flask, pandas, cx-oracle, sqlalchemy), Docker, Kubernetes, AWS (API Gateway), Elastic Search, Oracle, Gitlab
Within the Machine Learning & Data Lab team, I contributed to the development of the AI offer. I carried out internal R&D work and participated in missions with external clients.
Mission 1 : review of the state of the art of Deep Reinforcement Learning with an application to autonomous driving. Tools: python, tensorflow, keras, pytorch, opencv, torcs, airsim.
Mission 2: implementation of a scanned contract processing tool for a player in the pharmaceutical industry. Tools: python, jupyter notebook, tesseract ocr, nltk, tensorflow, glove.
Within the "Centre de Compétences d'Informatique Cognitive" (Skill Center of Cognitive Computer Science), I carried out POCs (prrofs of concepts) on the use of NLP to analyze customer verbatims. Tools: Python, NLTK, Gensim, Keras, Tensorflow, Pandas.
I contributed to the development of conversational agents intended for Orange employees. Tools: IBM Watson, dialogflow (Ex api.ai) from Google, python, keras, tensorflow, pygal.
Within the Signal & Communications department, I carried out research work on Spectral Clustering algorithms which resulted in the publication of a conference paper.
My mission was to implement a similarity function (kernel) for these algorithms and evaluate its performance. Tool: matlab.
