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Qikai Alex G.

data scientist / machine learning engineer

Paris, France

  • 48.8546
  • 2.3477
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Préférences

Déplacement
Peut faire la totalité d'une mission dans vos locaux

Vérifications

Influence

Github

Github : qikaigu qikaigu
  • 7 Followers
  • 24 Repos
  • 0 Gists

Kaggle

Kaggle : Qikai Qikai
  • Expert Tier
  • 4026 Rang
  • 2 Bronze
  • 0 Argent
  • 0 Or

Stack Overflow

Stack Overflow : Qikai Qikai
  • 26 Réputation
  • 6 Bronze
  • 0 Argent
  • 0 Or

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Compétences (18)

Qikai Alex en quelques mots

6+ years of experience in building end-to-end machine learning applications, solid fundamentals of data structures and algorithms. Cross-functional: be able to exchange with data analysts, data engineers, backend engineers and product teams.

I can help you build a scalable end-to-end machine learning applications on AWS. Leave me a message if you are looking for long term collaboration or want to rapidly prototype an MVP during a weekend.

Expériences

novembre 2018 - Aujourd'hui | Paris, France

Cinéma & audiovisuel

M6 Digital Distribution- M6

Data Scientist

Automated Machine Learning Platform
• Build a general-purpose automated Machine Learning platform based on Apache Spark framework.
• Build a cross-platform (desktop, mobile and TV) lookalike audience extension system on top of the general-purpose ML platform, which extends the audience reach up to 6 times larger than the base audience.
• Build a video recommender system on top of the general-purpose ML platform serving millions of users.
mars 2014 - septembre 2017 | Paris, France

E-commerce

A little Market - Etsy France

Data Scientist

Search Ranking
• Created the first Machine Learning powered application for millions of unique items on alittlemarket.com.
• Designed and developed a user behavioral data collecting system with Node.js and Elasticsearch.
• Developed a unique item purchase predictive model in Python(scikit-learn) and an Algolia reranking process.
• Deployed the predictive model in production as API using Flask.
• Designed and monitored Key Performance Indicators in Google Analytics and internal tools.
• Increased revenue by 15% (A/B test).

Recommender System
• Implemented a content-based recommender system with Spark Scala for millions of unique items.
• Parallelized batch jobs by using MapReduce programming model.
• Reduced job duration by optimizing algorithm's time complexity.

Autocomplete Suggestions
• Built a pipeline in Python for extraction and spelling correction of e-commerce expressions in French.
• Built a parallelization tool to reduce processing time with Python multiprocessing.

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