About Me

Hi, I'm Alex Ingberg

Data Scientist & ML Engineer.

Researching and analyzing data in various projects on my spare time.

Music lover, travelling fanatic, an amateur photographer and also a playlist compiler.

Drop me a line!


Bewildering Brain

  • An exploration of Markov Chains and RNNs (Recurrent Neural Networks), a comparison and analysis of which one outputs better results and how they both perform when predicting the lyrics of Bob Dylan (or Luis Alberto Spinetta in the Spanish version). Pulled lyrics from Genius API and guided myself with Spotify’s Web API.

  • Bewildering Brain: Bob Dylan's version (in English)
  • Oraciones artificiales: Luis Alberto Spinetta's version (in Spanish)
  • Article published in La Nacion, Argentina's most prestigious newspaper
  • Article published in Silencio.com.ar, a music medium from Argentina
  • Spotify ReWrapped

  • Pulling data from my Spotify and Last.fm accounts using their APIs, I did some time series analysis to check which were my real stats and see if what Spotify told me in my Spotify Wrapped end-of-year summary was correct. Also did some interesting data visualization to help explain my insights.

    Music Magal

  • MusicMagal is a group recommendation system that recommends n music tracks to a group of m users taking all of the m users preferences into account. Used last.fm data, an alternating least squares model and item2vec embeddings. After computing and when the resulting playlist is output, we create a real playlist using Spotify Web API.

    My Resume

    • Latest work experience

    • Senior ML Engineer

      Dynamic Yield (MasterCard): 2023 - Current

      Working with Computer Vision algorithms from HuggingFace’s repositories to develop a recommendations pipeline using Visual Similarity. Python, K8S, Airflow, Celery, AWS

    • ML/MLOps Engineer & Data Scientist

      Outbrain: - 2019 - 2023

      Main developer and owner of various internal products that helped data scientists automate their work, allowing them to deploy Machine Learning models in production at a large scale. Managed to improve the Data Science cycles speed in the company by 10x by orchestrating the training, deployment and ABtesting cycles through Airflow-based Python-coded tools. End to end responsibilities: backend and frontend development, Data Science research with field-aware factorization machines, MLops & product management.

    • Data Engineer

      Namogoo: 2018 - 2019

      Data Infra & ML Engineer: carried on projects on algorithms and data pipeline optimization from research all the way to production. Amazon Suite: Redshift, RDS, S3, SQS, Elasticsearch. Microsoft Azure. Python development.

    • Previous experience available on my LinkedIn page.

    • Education

    • Data Science Fellow

      Israel Tech Challenge: 2017 - 2018

      An intense fellowship for CS or engineering graduates with at least two years of experience in the industry, to acquire advanced tech skills in Israel. Syllabus contains data science tools as machine learning, deep learning, and data visualization.

    • MSc and BSc, Software Engineering

      Universidad de Buenos Aires: 2011 - 2016

      6 year program (equivalent to MSc & BSc). Oriented to production systems. My optional courses were mostly based on artificial intelligence and machine learning.

    Drop me a line!