seahyc

[0.0-1.4] Welcome to this Classics episode.
[1.7-4.0] Classics are my favorite episodes from the past 10 years,
[4.2-5.0] published once a month.
[5.4-7.6] These are end-of-one conversations with end-of-one people.
[8.1-11.3] Brad Jacobs' simple principle of think big, move fast
[11.3-12.6] is one I think about often.
[13.0-14.3] He is a true force of nature,
[14.4-15.8] and I hope you enjoy this episode.
[18.6-19.8] Hello and welcome, everyone.
[20.0-22.2] I'm Patrick O'Shaughnessy, and this is Invest Like the Best.

seahyc

Rollup Strategy Insights — Transcript & Book Analysis

Compiled from three video transcripts, one podcast transcript, and one book covering acquisition strategies, capital structures, and operational playbooks from Sarah Moore (eggcartons.com), the retelling of her story on My First Million, and Brad Jacobs (serial acquirer of 8 billion-dollar companies).

Sources

#	Title	Video	Raw Transcript
1	How I Bought A Multi-Million Dollar Egg Carton Business For $0 — Sarah Moore	YouTube	video1_clean.txt
2	How This Harvard MBA Bought A $50 Million Dollar Business For $0	YouTube	video2_clean.txt

seahyc

Brief

Given what you know about Glints' current data maturity, come up with a plan of what you would do in your first 90 days as the Head of Data.

Present it as a written document that can be understood as a standalone document. We'd read it first, and then have a discussion about it in our next call. Make it well-structured and realistic, something you'd actually act on were you to join us.

It is 100% ok to make reasonable assumptions, just spell them out in the plan. The current team comprises 2 data scientists working on job-talent matching and 3 data engineers working on our data warehouse - you'd have to take into account hiring latency if you plan to expand the team. 1 recommendation is to plan out for different resources scenario.

If you're missing any critical information, feel free to reach out to us, and we'll patch you in. In fact, we encourage you to email us at least 1 batch of clarifying questions, just like you would in a real job, and we'd answer them promptly

seahyc

Fulfilment of Specs and Implementation Rigor

• Does the app fulfill the given requirements?

Complexity/Code Quality

• Is it easy to understand how the code works?
• Are things organized in a sensible, consistent manner?
• Do the files have an appropriate length?
• Are there no unnecessary DRY violations?
• Is the code not too tightly coupled? Are concerns separated? Would it be easy to modify the code?
• Do code-units have an appropriate length?

seahyc

Humans for what they do best, AI for the rest

A core part of Glints' business model is our recruitment service, which is staffed by recruiters. Recruiters are the go-bewtween for employers and talent. They first collect job requisition details from the employers, before filling and managing a pipeline of candidates through the interviewing circuit. This work involves a lot of manual work, such as selling, coordination, KPI tracking, funnel management and relationship management over calls and messaging apps like Whatsapp.

We would like you to rethink this workflow such that it is an order of magnitude more efficient, effective and engaging for employers, candidates and recruiters. Using any combination of visual formats, paint us a vision of how that experience looks like from all 3 parties' perspectives. You can attempt some reasonable definitions of efficiency, effectiveness and engagement in this context.

We would be evaluating the depth of the insights, the feasbility of the approach (it can be a bol

seahyc

Good Day,

Thank you for applying for the position of Data Engineer at Glints. The following describe the Technical Assessment requirement for this position.

Problem Set

A key part of a Data Engineer’s responsibilities is maintaining the serviceability of Data Warehouse. To achieve this, you will need to understand the set up and operation of a basic Data Warehouse.

In this technical assessment, you are required to submit the setup for the data pipeline of a basic data warehouse using Docker and Apache Airflow.

seahyc

Brief

For us to assess your technical skills, you can attempt one of the following tasks based on your technical domain and take us through a demo of the functionalities.

Backend - https://gist.github.com/seahyc/97b154ce5bfd4f2b6e3a3a99a7b93f69

Frontend - https://gist.github.com/seahyc/628ed57fcaa2ee8e55e570cd220a553e

Mobile - https://gist.github.com/seahyc/a937011e576bc32fe1b54ea8ab8cf52f

seahyc

Simple Twitter App

Implement a simple Twitter app using Firebase Auth and Cloud Firestore.

On first launch, the app lets users sign in with Firebase using email and password. (Note: avoid Google SSO to ease local testing)

After sign in, the app shows a page where the user can:

• Type in a tweet with 280 characters limit
• Save this along with the current time into Firestore

seahyc

Buying Frenzy

You are building a backend service and a database for a food delivery platform, with the following 2 raw datasets:

1. Restaurants data

Link: https://gist.github.com/seahyc/b9ebbe264f8633a1bf167cc6a90d4b57

This dataset contains a list of restaurants with their menus and prices, as well as their cash balances. This cash balance is the amount of money the restaurants hold in their merchant accounts on this platform. It increases by the respective dish price whenever a user purchases a dish from them.

seahyc

[
    {
        "cashBalance": 700.7,
        "id": 0,
        "name": "Edith Johnson",
        "purchaseHistory": [
            {
                "dishName": "Olives",
                "restaurantName": "Roma Ristorante",
                "transactionAmount": 13.18,