Data Scientist

Teaching to Master students the art of data science, AI and can those leverage business.

Context: Students are from management and marketing field,

Goals: - My role was to give them the theorical and practical knowledge of data science and AI to give them the ability to understand, setup and even make a data science project in a professional ecosystem.

- Give the student the knowledge to interact with the data science team and to understand all the process of a data science / AI project.

Level: Students are in their last year of Master degree

As a Lead Datascientist in freelance I succefully helped the team to define and build two main projects in machine learning apply to marketing.

Project 1: Score the likelihood of a customer to buy a product

---- Context: - 6 year of user activity logged in a DataLake (hdfs)
- 1 year of user activity in the website logged in google analytics
- Cross Domain products ( Food, Home, Jewelry .... )
- About 300k active users per year

---- Goals: - Increase the cross selling by targeting the wrigth user for the wrigth product when a user didn't buy the kind of product (e.g. Selling chocolate when the user only buy jewelry)
- Be able to define the value of the coupon for each customer ( higher is the attraction lower is the value of reduction )
- Understand the behavior of customers

Solutions: - A model that score the probability of a user to buy a type of product next month knowing his past (types of products are defined by the marketing team)
- A model that map users and products into a semantic space that models the behavior and interactions between user / user and user / item

Work Done : - Lead the team to success
- Formation of the data science team
- Extraction of data in the DataLake (Spark 2)
- Extraction of data in google analytics (Python + Google Analytics)
- Feature Cleaning and Feature Extraction, Feature Engineering
- hyperparameter and parameter optimization + Model selection
- 1 classification model with probability outputs (H2O + Sklearn)
- 1 recommendation model with score output + mapping (TensorFlow) Deep recommender systems

Keywords : collaborative filtering, Google Analytics Api, Hive feature extraction, Deep Feature Extraction

Project 2: Customer Segmentation on buying behaviors for Food Products

As a Lead Data Strategist in this emailing marketing compagny I built from scratch the infrastructure.

Work Done:
- Coordinate the technical team and the interactions with the commercial team.
- Define the scope of project to enhance business with data
- Define the digital strategy roadmap
- Build the infrastructure of servers that send mails ( more than 300k emails send by day ), the infrastructure was built in a way that optimize speed, security and reputation of ips.
- Develop a software to manage emails segments, work on commercial email, Bulk emailing, statistics reports.
- Addons for IP rotation, IP reputation monitor, Speed per IP based on reputation and past actions.
- Develop Business Intelligence tools for decision making.
- Build from scratch Machine Learning tools to segment customers by their behavior.