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README.md

Work at Olist - BS&A

Olist is the largest department store of Brazilian marketplaces. We connect small businesses to channels without hassle and with a single contract. We have connected more than 4.1 thousand sellers to stores like Americanas.com, Ponto Frio, Walmart, Submarino, Mercado Livre, Amazon, among others.

Business Science and Analytics (BS&A)

The Olist Business Science and Analytics (BS&A) was structured to subsidize business strategies and improve the operational efficiency through the use of analytics techniques and to be a trustworthy source of information. The BS&A team consists of data scientists, data engineers, data analysts, business analysts and developers.

You may read more about the BS&A structure here (in portuguese):

  1. Como estruturar uma equipe de análise de dados em uma startup? — Parte 1 <-> Entenda como criamos a área de Business Science & Analytics, que reúne os profissionais de análise de dados no Olist. Prós e contras de uma estrutura integrada e de uma estrutura federada.
  2. Como estruturar uma equipe de análise de dados em uma startup? — Parte 2 <-> Detalhes das tarefas e funções existentes em BS&A e como ela se encaixa dentro da empresa.
  3. Como estruturar uma equipe de análise de dados em uma startup? — Parte 3 <-> Job descriptions de cada função de BS&A e primeiras impressões sobre o funcionamento da área.

This repository contains instructions to solve problems that are used to evaluate the candidate skills. It's important to notice that satisfactorily solving it is just a part of what will be evaluated. We also consider other disciplines like data understanding, data visualization skills, statistics knowledge, machine learning understanding and its correct use, documentation, design and coding best practices.

How to participate

  1. Make a fork of this repository on Github;
  2. Follow the instructions of README.md (this file);
  3. Deploy the project if necessary. Here are some tools we recomend:
  4. Apply for the position at our career page with:
    • Link to the fork on Github;
    • Link to the deployed project.

Work at Olist BS&A - Test

Dataset

Olist has released a public dataset on Kaggle. The dataset contains information from 100k orders from 2016 to 2018. Its 21 supportive features allows viewing an order from multiple dimensions: from order status, price and freight performance to customer location, product attributes and finally reviews written by customers.

This is real commercial data, it has been anonymized, and references to the companies and partners in the review text have been replaced with the names of Game of Thrones great houses. Read carefully the dataset overview and understand all data available.

Main objective

Tell us something we don't know. Which business value would you create for Olist with this data?

Requirements

You may want to solve different types of problems with this dataset. Each job description inside Business Science & Analytics requires a different set of skills and this dataset provides enough data to everyone work on it. Choose the position that best suits you and have fun with the data. Bellow are some examples of things you might want to do, but feel free to use your creativity.

You are not required to do everything listed bellow... remember that quality is more important than quantity.

Language Requirements: We like to experiment new things! Feel encouraged to solve the test with the tool you like the most. We would love to see solutions using languages such as R, Julia or Scala.

1. Business Inteligence Analyst and Data Analyst

Your job is to build business KPIs from the data and find relationships with the real world. Build dashboards or create some reports. Tell us what is important and why, build some metrics and help us make better decisions with data. You might want to create some impressive data visualizations. Remember this is real data, so we expect you to extract meaning from it and show us which events are important, how customers from certain regions are better or worse, or yet which products should we focus our sales efforts. Show us that you master Excel, knows a lot of SQL and understand the basics of Python.


2. Data Scientist

Your job is to build robust statistical analysis with the data. Do some feature engineering, create models to predict sales or classify comments. Remember that you might have to put models into production environment, then make your code ready to get a new unseen json record and predict the outcome from that data. Discover why customers are happy or unhappy or tell us how to improve delivery performance. You name it... there is a ton of thins that you might do with the data. Just show us that you are a Pandas Ninja, a Jedi Master of scikit-learn and that you are able to build fantastic visualizations. Statistics and SQL are also important skills.


3. Data Engineer

Your job is to build our pipes of data. You breath ETL. Complement the dataset with some external data or create a crawler to aquire information from third party websites or APIs. Do tons of feature engineering. Set-up a relational database (or a NoSQL) and input the treated data there. Create some complex SQLs to extract and transform data. Show us that you are fluent at SQL and Pandas, have knowledge of Python Scripting and that you are able to do complex and meaningful work with data.

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