AWS Solutions Architect - CCoE

• Jun 2022 - Present

Cloud Solutions Architect

• May 2021 - Jun 2022

Cloud Solutions Architect - CCoE - SMART AWS

• May 2021 - Jun 2022

Cloud Data Engineer

• Nov 2020 - Apr 2021

Project: Set up of a Data platform to centralize, process, manage insurance data, and offload legacy systems on AWS.Achievement:• Contributed to designing the infrastructure layer of the platform: S3 as a data lake, Redshift as a data warehouse, Glue for cataloging the data, Step Functions for workflows• Developed a sensitivity-based anonymization framework in spark to handle a very sensitive Data such as DSN data (Déclaration Sociale Nominale)• Ensure the Data Security at rest (KMS encryption) and in flight (SSL)• Implemented elements of the platform's infrastructure with Terraform• Designed and implemented the batch ingestion pattern of the data• Implemented the data cataloging pattern: used Glue’s Classifiers, Crawlers, and jobs for this pattern• Designed and implemented ingestion and cataloging workflows with Lambda functions and Step Functions• Designed and implemented the data traceability pattern• Developed a Spark jobs for data processing and extractions on AWS EMR Technologies: • Java (For application components & Lambda functions), • AWS environment, Redshift, EMR, CloudWatch, Serverless: S3, DynamoDB, Glue, Step Functions.• Spark 3 for Data processing• Infrastructure as code: Terraform• DevOps toolchain: Git for Code versioning, Jenkins-Maven-Ansible for CI/CD

Cloud Big Data Consultant

• Oct 2019 - Apr 2021

MUTEX Officiel: Starting from November 2020.RATP Project : from October 2019 to October 2020 : • Developed Spark Streaming application in Scala that connects to Kafka and fetch data in real-time.• Used Spark-Streaming APIs to perform necessary transformations and actions on the fly for building the common learner data model which gets the data from Kafka in near real time and Persists into Cassandra, deployed in AWS cluster.Technical environnement: Scala, Python, Shell, spark , AWS, Oozie, Hive/Impala/Tez, HDFS, Zeppelin, Cassandra, ELK.

Data Scientist - Textile B2C, Telecom, Software Testing

• Oct 2017 - Oct 2019

• Build predictive models by using state of the art Machine Learning algorithms such as Random Forest, XGBoost, Light GBM, etc• Identify valuable data sources and perform feature engineering processes.• Propose solutions to enhance the Data Quality.• Collaborate and work closely with product development teams.• Presenting information using appropriate data visualization techniques. • Build predictive models by using state of the art Machine Learning algorithms such as Random Forest, XGBoost, Light GBM, etc• Identify valuable data sources and perform feature engineering processes.• Propose solutions to enhance the Data Quality.• Collaborate and work closely with product development teams.• Presenting information using appropriate data visualization techniques.

Data Scientist - Sales, Fast Fashion, Retail, and Product Analytics

• Oct 2017 - Dec 2018

Sales prediction and Markdown Optimization for German - Fast Fashion - Retailer.• Sales Prediction and clearence pricing optimization in Fast Fashion context.• Collection, aggregation, Transformation for all the given data from different sources : ERP, Transactions, resellers…• Responsible for maintaining quality reference data in Oracle by performing operations such as cleaning, transformation and ensuring Integrity in a relational environment.• Develop a predictive model using Machine Learning algorithms, in order to perform Markdown Optimization. Technical environnement: SQL, Python, Einstein Analytics, Clustering (Kmeans; to represent the canibalization effect).

Data Scientist - Risk Management, Network Analysis - Telecom

• Mar 2017 - Sep 2017

Risk classification & Interconnexion between risks :• Master the world of risks at Orange (strategic, financial, operational and compliance risks)• Perform Risk analysis to establish the links between them by exploring all the existing data.• Modelling the links between risks to identify the major risks.• Use of the power of data analysis to inform strategic decisions and increase the speed of decision making.• Improvement of decision making by developing Machine Learning algorithms and behaviour prediction scenarios.• Anticipate the risks and achieve strategic objectives by working closely with Risk Management team at London.• Design of graphical interfaces to facilitate decision-making.Technical Environment : SQL, Python, Data Visualisation, Network Analysis, Machine Learning, Tableau software.

Data Scientist - Marketing Quantitative Analyst, Client segmentation.

• Jun 2016 - Sep 2016

• Selection and validation of relevant data for analysis.• Marketing targeting and conversion rate optimization (A/B testing).• Implement and ensure statistical modelling of data.• Perform depth data analysis to better understand the customer need.• Accelerate customer data processing time and provide real-time information.Technical environment: Python, Classification, Clustering, Big Data. • Selection and validation of relevant data for analysis.• Marketing targeting and conversion rate optimization (A/B testing).• Implement and ensure statistical modelling of data.• Perform depth data analysis to better understand the customer need.• Accelerate customer data processing time and provide real-time information.Technical environment: Python, Classification, Clustering, Big Data.

Java Software Engineer

• Sep 2015 - Jan 2016

Developing Java Application connected to a Mysql database :• Elaboration of detailed specifications and associated models.• Development of an application to manage and identify the manufactured products and materials used.Technical environment: JAVA, MySQL, SQL, UML. Developing Java Application connected to a Mysql database :• Elaboration of detailed specifications and associated models.• Development of an application to manage and identify the manufactured products and materials used.Technical environment: JAVA, MySQL, SQL, UML.