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Amine BoujidaAB

Amine Boujida

Data scientist | Applied scientist | ML-Ex Amazon

€611/day
Paris, FR
3-7 years

Average response time: 1 hour

About Amine

Senior Data Scientist with expertise in NLP, time series, and ML/DL techniques. Skilled in Python, Java, and AWS, with a background in large-scale data and statistical modeling.

Visit my Portfolio to explore my open source projects : b7amine.github.io

  • French

    Native or bilingual

  • English

    Fluent

Can work on-site
Paris (up to 50km), Nice (up to 50km)

Experience

  • Remote
    Senior ML Scientist
    April 2025 - Today (1 year and 2 months)
    Took a career break due to urgent personal reasons abroad. During this time, I'm working independently as a contractor on a few short-term remote projects while also focusing on personal initiatives and learning. Registered as auto-entrepreneur in France. Responsibilities include :
    • Provide guidance on modeling strategy
    • Advise early-stage teams on ML system architecture, Spark - Python - SQL - Pytorch
  • Amazon Ads
    Data Scientist
    February 2023 - March 2025 (2 years and 1 month)
    London, UK
    As a Data Scientist at Amazon Ads, I develop and implement advanced data-driven strategies and ML algorithms to enhance ad relevance for both in-store and offsite placements, contributing to a platform serving millions of advertisers and reaching hundreds of millions of customers globally. My role includes leading team initiatives and influencing broader decisions on targeting strategies. Project Highlights
    • Contextual Targeting on Twitch: Developed privacy-preserving contextual targeting solutions for Twitch, introducing audio-based content analysis methods and new statistical frameworks for con tent relevance using Monte Carlo permutation tests. Built embedding-based tools to track content stability across streaming sessions, showing strong correlations with ad performance metrics and en abling effective targeting without user identification. Led the entire process from research through to production, achieving a 14% revenue increase in controlled experiments.
    • Audience Targeting Optimization: Identified and addressed performance bottlenecks in audience tar geting channels , coming mainly from imbalance in the demand distribution and attendance bias. Implementing a recommender system that boosted audience engagement and contributing to a 12% increase in CTR.
    • Content Analysis and Crawling Optimization: Led initiatives to analyze and optimize web crawling strategies, identifying significant opportunities for improvement. Successfully implemented a con trastive learning approach to exploit these opportunities
    • Mentorship and Collaboration: Mentoredjunior team members and interns Co-Authored internal papers AWS - Spark - Java - Pytorch - Recommender Systems - Contrastive learning - 2 Tower Models
    • Audio signal processing - LLMs
  • ENGIE B2C
    Applied scientist
    September 2020 - February 2023 (2 years and 5 months)
    Paris, France
    Engie, a market leader in residential electricity, serves over 7 million households. I leveraged smart meter and customer datasets to enhance customer insights and optimize energy consumption through web and mobile services. As a Data Scientist on a multidisciplinary team of 11, my responsibilities included data analytics, designing modeling solutions, and supporting production deployments.
    • Conducted several studies : Assessing Covid-19 impact on household energy consumption , identifying a positive correlation between churn rates and end of the year regularization bill
    • Developed a multi-granularity electricity consumption forecaster (Yearly , monthly , daily , hourly ). +21% coverage and -54% in the regularization bill. Self supervised approach to enhance the model's resilience against data anomalies .
    • Developed a simple yet effective client segmentation approach
    • Hypothesis testing during new products launches C3AI - Spark - TensorFlow - Time Series modelling - Causal inference - Signal processing - Hypothesis testing - AWS

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