rloredo / dbt-snowflake

dbt-snowflake contains all of the code enabling dbt to work with Snowflake

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.