Mohamed D.

Data Scientist

690 dollar
Freelancer
7 ans
Paris, FRANCE

Mon expérience

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LegalPlaceJuly 2019 - Présent

Data Engineering and Analysis: I created the data pipeline (ETL) from scratch to store data from different sources: payment transactions (Paypal, Stripe, Alma etc..) Mixpanel, Google and Bing Ads, internal data. I created dashboards for financial, marketing and product teams. AWS services used: Lambda, Athena, Quicksight, Glue, S3, and CloudWatch.

Model Training/Prediction: I built a deep learning model to classify and extract relevant entities from french employment contracts. I created the pipeline from scratch, starting from data collection, annotation and cleaning, model training, validation, testing, and deployment on AWS, achieving 85% F1-score.

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LeakmitedMarch 2019 - April 2019

Detection and prediction of water pipe leaks using satellite (SAR) images and machine learning techniques.
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Entrepreneur FirstSeptember 2018 - January 2019

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
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DoleadFebruary 2018 - August 2018

Analyze and improve search engine advertising campaigns using statistical and machine learning techniques.
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LIMSIMarch 2017 - August 2017

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.

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InriaFebruary 2016 - September 2016

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​.

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Grenoble Computer Science LaboratoryFebruary 2015 - May 2015

Topic: Using Resources from a Closely-related Language to Develop ASR For a Very Under-resourced Language: A case study for Iban language.

Accomplishments: My reported results are included in a paper published at Interspeech 2015 conference (See publications section).

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ValeoMarch 2013 - September 2014

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.

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M-SystemsJanuary 2012 - December 2012

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.

Mes compétences

Business Intelligence

Statistica

Software testing

Test Driven Development (TDD), Hardware testing, Integration testing, Unit testing

Mobile

Embedded Systems

IT Infrastructure

Amazon EC2, Git, Linux, Docker, Amazon SageMaker

Databases

MongoDB

Others

Research, AUTOSAR, Artificial Intelligence, Twitter, Natural Language Processing (NLP), GitHub, Data analysis, Data Science

Languages

C++, Java, JavaScript, TypeScript, C/C++, Python, Regex, SQL

Analysis methods and tools

DevOps, Agile Methodology

Big Data

Spark

Embedded and Telecom

FPGA

Technologies

AWS, Flask, Machine Learning, Matplotlib, NumPy, Pandas

Machine Learning

PyTorch, Keras, Scikit-Learn, TensorFlow, Neural networks, Deep learning

Mes études et formations

Courses - LinkedIn

Master of Science, Informatics, Science - National Higher School of Computer Science and Applied Mathematics of Grenoble2016 - 2017

M1 Masters of Science in Informatics at Grenoble (MOSIG), Computer - Grenoble Alps University2015 - 2016

Certificates - Coursera2014 - 2016

Bachelors Degree, Computer Systems and Engineering - Alexandria University2007 - 2012