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rloredo/README.md

Hi there 👋

I'm Rodrigo, a data analyst, scientist, engineer, guru, sherpa... currently living in Amsterdam, NL (originally from Argentina).

I’m currently working at Vinted as a Analytics Engineer.

Before that, I worked at Felyx as an Analytics Engineer too. I've also worked at Amberscript setting up the analytics-BI department. I was in charge of the whole analytics ecosystem, from ingestion to visualization and insight-sharing. I've also worked as a Data Scientist for Tiendanube & Nuvemshop, a B2B, SaaS company, for almost two years. In that job I had to handle big amounts of data, implement supervised and unsupervised ML models, report insights to key stakeholders, and lead a team of four data scientists. You can read a little bit more about those projects here.

My journey to Data Science began when I started my Ph.D. in psycho and neurolinguistics. In that process, I realized that what I loved most was designing and implementing experiments, and modeling data to analyze the results. Thus, I started studying descriptive and inferential statistics, machine learning, and learning to code.

In my free time, I like to read, study, and write about data science & analytics, human skills, and other things. I also love outdoor sports like rock climbing, sailing, and playing football. I also enjoy building things, woodworking, and gardening. I fixed a 12ft. sailboat and I've been building a 14ft. wooden boat!

Projects

I have worked on, or supervised projects about:

  • Topic modelling and tagging of customer support conversations
  • Customer clustering using Amplitude events and product configurations
  • Chatbot for customer support
  • Data Science toolkit for our team
  • Quality lead predictor: predict if a trial will pay after trial period
  • Quality partner predictor: predict if a commercial partner will bring a new client
  • Churn analysis: failed predictor project =(
  • Perfect client modelling to find out what our best clients do and how we can make recommendations based on those practices to other clients
  • Market basket analysis for apps marketplace
  • Customer journey visualization using Amplitude events and sankey diagrams
  • A/B tests of user onboarding
  • A/B tests of e-commerce checkout page
  • Crawling of instagram and twitter metrics, competitors, churned clients, etc.
  • Attribution models for performance marketing
  • Allocation of revenue and financial consolidation
  • Unit economics and PnL (CAC, LTV, etc.)
  • And many more!

Gists

Check out my gists with useful snippets for NLP and discrete event simulations.

Personal website

In my blog I share some thoughts and stories about Data Science and Analytics.

Pinned Loading

  1. elementary-data/elementary elementary-data/elementary Public

    The dbt-native data observability solution for data & analytics engineers. Monitor your data pipelines in minutes. Available as self-hosted or cloud service with premium features.

    HTML 2k 168

  2. git-jira git-jira Public

    A git addon to manage jira from git

    Python

  3. whatido whatido Public

    Resources for my blog: whatido.com.ar

    Jupyter Notebook

  4. LDA-explanation-and-example LDA-explanation-and-example Public

    A quick intro to LDA with examples

    Jupyter Notebook

  5. pln-uba-2019 pln-uba-2019 Public

    Forked from PLN-FaMAF/pln-uba-2019

    Introducción al Procesamiento de Lenguaje Natural - UBA 2019

    Jupyter Notebook

  6. StatisticalAnalysisExp StatisticalAnalysisExp Public

    Statistical Analysis with R: Rapid access to scalar implicatures