Bienvenue sur le profil Malt de Mohamed !
Localisation et déplacement
- Localisation
- Paris, France
- Peut travailler dans vos locaux à
-
- Paris et 50km autour
Préférences
- Durée de mission
-
- ≤ 1 semaine
- ≤ 1 mois
- entre 1 et 3 mois
- Secteur d'activité
-
- Santé & bien-être
- High tech
- Environnement
- Energie
- Education & e-learning
+7 autres
- Taille d'entreprise
-
- 11 - 49 personnes
- 50 - 249 personnes
- 250 - 999 personnes
- 1000 - 4999 personnes
- ≥ 5000 personnes
Vérifications
Charte du freelance Malt signée
Consulter la charte
Influence
Chargement...
Stack Overflow
Langues
Catégories
Compétences (32)
- BigData
-
- Databases
-
- Data Science
-
-
Débutant Intermédiaire Confirmé
-
Débutant Intermédiaire Confirmé
-
-
Débutant Intermédiaire Confirmé
- Frameworks
-
Mohamed en quelques mots
I am a Senior Data engineer & ML Engineer with 7 years of professional experience. I am a
software engineer who switched to data science and then to data engineering. I studied at ENSIMAG and Grenoble Alpes University. I also received entrepreneurship training at Entrepreneur First.
I worked at Air Liquide, DisneyLand Paris, ManoMano, LegalPlace and Valeo among others.
Tech Stack:
- Python, SQL, AWS, Snowflake, Airflow, Terraform, Docker, Gitlab CI/CD, Apache Kafka.
- Pytorch, Keras, Scikit-learn, SciPy (Numpy, Pandas, Matplotlib).
- NLP: Transformers, SpaCy, Flair, NLTK, RegEx.
Services provided:
Data Engineering:
- Creating data platform from scratch for startups on AWS.
- Maintaining data platforms (pipelines, infrastructure) for existing platforms.
- Creating data pipelines.
Machine Learning Engineering:
- Creating/enriching/cleaning datasets.
- Training, validating and testing ML models, and especially NLP models.
- Deploying and monitoring models in production.
My CV online: standardresume.co/r/dyabmo
software engineer who switched to data science and then to data engineering. I studied at ENSIMAG and Grenoble Alpes University. I also received entrepreneurship training at Entrepreneur First.
I worked at Air Liquide, DisneyLand Paris, ManoMano, LegalPlace and Valeo among others.
Tech Stack:
- Python, SQL, AWS, Snowflake, Airflow, Terraform, Docker, Gitlab CI/CD, Apache Kafka.
- Pytorch, Keras, Scikit-learn, SciPy (Numpy, Pandas, Matplotlib).
- NLP: Transformers, SpaCy, Flair, NLTK, RegEx.
Services provided:
Data Engineering:
- Creating data platform from scratch for startups on AWS.
- Maintaining data platforms (pipelines, infrastructure) for existing platforms.
- Creating data pipelines.
Machine Learning Engineering:
- Creating/enriching/cleaning datasets.
- Training, validating and testing ML models, and especially NLP models.
- Deploying and monitoring models in production.
My CV online: standardresume.co/r/dyabmo
Expériences
Air Liquide IT - GIO Département GDO - Air Liquide
Energie
Data Engineer / Architect - En tant que freelance
Creation of a POC for a data quality tool for Air Liquide’s data-lake Core Models on AWS.
EURODISNEY ASSOCIES SAS - EURODISNEY ASSOCIES SAS
Divertissements & loisirs
Data Engineer - En tant que freelance
- Migration from different enterprise data warehouses towards a cloud data platform (AWS S3, Glue, Snowflake).
- Developing and maintaining data pipelines.
- Creating data models and iterating with different stakeholders.
- Developing and maintaining data pipelines.
- Creating data models and iterating with different stakeholders.
ManoMano - Mano Mano
E-commerce
Senior Data Engineer
Member of the Data Platform team in the data Train (SAFe organization).
Accomplishments:
1. Ingesting new tables and events from micro-services via Kafka and exposing them into Snowflake for various data squads.
2. Contribute to Kafka cluster migration and detecting data discrepancies.
Accomplishments:
1. Ingesting new tables and events from micro-services via Kafka and exposing them into Snowflake for various data squads.
2. Contribute to Kafka cluster migration and detecting data discrepancies.
LegalPlace - LegalPlace
Conseil & audit
Data Engineer & Data Scientist
Responsible for all data science and data engineering issues at LegalPlace.
Managed/mentored a data science intern for 6 months.
Accomplishments:
1. Created an ETL pipeline from scratch to store data from various sources: Salesforce, Paypal, Stripe, Mixpanel, Google/Bing/FB Ads, production database. Created dashboards for financial, marketing and product teams.
2. Built an NLP deep learning model to classify and extract relevant entities from french employment contracts. Performed data collection, annotation, cleaning, model training, testing, and deployment on AWS, achieving 85% F1- score.
3. Created a document for Crédit d'impôt recherche (CIR) regarding NLP and Knowledge Graphs.
Managed/mentored a data science intern for 6 months.
Accomplishments:
1. Created an ETL pipeline from scratch to store data from various sources: Salesforce, Paypal, Stripe, Mixpanel, Google/Bing/FB Ads, production database. Created dashboards for financial, marketing and product teams.
2. Built an NLP deep learning model to classify and extract relevant entities from french employment contracts. Performed data collection, annotation, cleaning, model training, testing, and deployment on AWS, achieving 85% F1- score.
3. Created a document for Crédit d'impôt recherche (CIR) regarding NLP and Knowledge Graphs.
Entrepreneur First
EFPA1 Cohort Member
Extensive and focused hands-on entrepreneurship training. Co-founder selection, ideation, validating customer need/market, and going through a pre seed investment committee. Entrepreneur First brings together extraordinary people to build startups from scratch in London, Singapore, Berlin, Hong Kong, and Paris. EF funds individuals and help build co-founding teams, develop ideas, and accelerate through fundraising from the world's best investors. EF have built over 150 companies, have over 1000 alumni worldwide, and the portfolio has a valuation of over $1.5 billion. EF's major exits to date include Magic Pony, led by Rob Bishop and Zehan Wang, which was acquired by Twitter for a reported $150m only 18 months after the founders met on the EF programme. For more information about Entrepreneur First, check out: www.joinef.com
Dolead - Dolead
Data Scientist
Analyze and improve search engine advertising campaigns using statistical and machine learning techniques.
LIMSI
Machine Learning Research Intern
Topic: Talking-face Detection using Audio and Visual Modalities in TV Shows. Python, Keras and Scikit-Learn are used. Trained convolutional neural networks and long short-term memory networks (LSTM) to detect talking faces in videos, using both visual and audio modalities. Accomplishments: Showed that using a combination of visual and audio modalities for LSTM improves the performance over using either modality alone.
INRIA - INSTITUT NATIONAL DE RECHERCHE EN INFORMATIQUE ET EN AUTOMATIQUE (INRIA)
Machine Learning Research Intern
Topic: GPU Execution Time Prediction using Machine Learning and Analytical Modeling. Python, Scikit-Learn and R are used. Trained three different machine learning models to predict execution time of applications running on GPUs, and compared them with an analytical model. Accomplishments: Showed that machine learning approach provides more flexibility than analytical one, as some variables needn't be explicitly calculated. Published paper at IEEE-NCA 2016 conference.
VALEO - Valeo
Software Engineer
Developed standard embedded software components in C/C++. Performed unit testing, integration testing and hardware testing. Configuring AUTOSAR (AUTomotive Open System Architecture) modules, specifically microcontroller abstraction layer, and testing them on hardware boards. Accomplishments: Developed several software components such as SMS manager, eCall manager etc.. from scratch for eCall system (Emergency response to car accidents) and successfully tested them on hardware boards.
M-Systems
Co-Founder and Verification Engineer
Providing digital systems services: digital IP cores and verification IP cores: HDMI 4.0 stimuli generator & LEON3 processor configuration. Accomplishments: Received a cheque from one customer for our efforts in completing his project.
1 mission Malt
Consultez les avis de fin de mission de Mohamed
3 recommandations externes
Consultez les recommandations qu'a reçues Mohamed