Prediktiva

● Launching and scaling the first Data Science Agency of LATAM 

Prediktiva empowers startups and SMEs to leverage the power of Machine Learning to make intelligent forward-looking projections that drive tangible business outcomes - in less than a month.

Founder, Head of Data Science

Notion

•  Designing and implementing Notion productivity systems to enhance the operational efficiency of fast-growing startups

Notion Certified Consultant

Vega Coffee

•  led the finance department and all associated strategic and operational functions as the 1st CFO hire, 
•  implemented tech and process automation initiatives to scale operations across three countries,
•  provided ongoing support during due diligence of Bridge and Seed Rounds

Chief Financial Officer

Liftit

•  developed a detailed understanding of unit economics to increase profitability and organic revenue by 57%
•  led strategic finance, sales, marketing, and operations across 5 countries 
•  right hand to the CEO in raising a $14.3m Series A and $22.5m Series B

Ruta N Medellin

•  coordinated Tech acceleration programs with a total budget of USD 1.2m
•  redesigned program structures & updated the acceleration methodology
•  supported more than 50 Series A & Seed-stage startups

Accelerator Manager

Suyo PBC

•  set up and directed finance function from scratch, including financial modelling, FP&A, budgeting & reporting, KPIs & OKRs tracking
•  developed and allocated operational budgets for the national expansion plan
•  supported the CEO during Seed-Round due-diligence and negotiations

Head Of Finance

UniCredit

•  participated in the origination, structuring, and negotiation of USD 100bn+ project finance infrastructure transactions, including preparation of full-blown models, negotiation of term sheets and operations due-diligence

Infrastructure & Power Project Finance - Senior Associate

Drag-n-drop no-code pivot tables and interactive charts' creator that works in both Jupyter and R?

Check-out 𝗣𝗶𝗯𝗼𝘁𝗧𝗮𝗯𝗹𝗲𝗝𝗦! 

#datascience #datavisualization 

🦾 Paolo Perrone

10 YouTube Channels that will make you a full-stack Data Analyst 

Check out the Notion page in the comments to filter channels by topics of interest!

@freecodecamp 👉  https://lnkd.in/gnUT4kNt 
from freeCodeCamp 
Topics: Python, R, SQL, Statistics
Stats: 7.6m subs, 1.4k videos

@statquest 👉 https://lnkd.in/gY38Vsj6 
from Joshua Starmer PhD 
Topics: Statistics
Stats: 923k subs, 255 videos

@excelisfun 👉  https://lnkd.in/gHKu5MDS 
from Mike "excelisfun" Girvin
Topics: DAX, Excel, PowerBI, PowerQuery, Python, SQL, Tableau
Stats: 881k subs, 3.6k videos

@codebasics 👉  https://lnkd.in/grKiupQU 
from Dhaval Patel 
Topics: Math, Python, SQL, Statistics
Stats: 780k subs, 630 videos

@krishnaik06 👉 https://lnkd.in/gQWmQMYV 
from Krish Naik 
Topics: Interviewing, ML, SQL
Stats: 750k subs, 1.6k videos

@AlexTheAnalyst 👉 https://lnkd.in/gVvMVmQS 
from Alex Freberg
Topics: Excel, Interviewing, PowerBI, Python, SQL, Tableau
Stats: 462k subs, 207 videos

@HowtoPowerBI 👉 https://lnkd.in/g72Z-2t9 
from Bas Dohmen
Topics: DAX, PowerBI, PowerQuery
Stats: 125k subs, 266 videos

@TableauTim 👉https://lnkd.in/gwS4ghtd 
from Tim Ngwena  
Topics: Alteryx, DBT, Snowflake, Tableau
Stats: 47k subs, 401 videos

@vizwiz 👉 https://lnkd.in/gJ5iq9gj 
from Andy Kriebel
Topics: Tableau
Stats: 47k subs, 675 videos

@loresowhat 👉 https://lnkd.in/gciNCv7h 
from Lore - are you on LinkedIn? 😀
Topics: Excel, Interviewing, Python, SQL, Tableau
Stats: 9k subs, 69 videos

Got anything to add?

#dataanalyst #excel #sql #powerbi #python #tableau #ml #statistics 

𝗣𝘂𝘁 𝗱𝗮𝘁𝗮 𝗰𝗹𝗲𝗮𝗻𝗶𝗻𝗴 𝗮𝗻𝗱 𝗲𝘅𝗽𝗹𝗼𝗿𝗮𝘁𝗶𝗼𝗻 𝗼𝗻 𝗮𝘂𝘁𝗼-𝗽𝗶𝗹𝗼𝘁 𝘄𝗶𝘁𝗵 𝘁𝗵𝗶𝘀 𝗣𝘆𝘁𝗵𝗼𝗻 𝗹𝗶𝗯𝗿𝗮𝗿𝘆

No matter what kind of data analysis you're working on, there are always a bunch of little tasks that end up taking a lot of time

That's precisely where Klib comes in – by automating many of these repetitive, tedious tasks, it makes data cleaning and exploration a breeze

With Klib, you can quickly visualize missing data – represented by black dots in the first image, perform 1-click data cleaning, visualize correlations, distributions and categorical variables

Automating these tasks, not only saves you time but also helps you gain a deeper understanding of the dataset you're working with

In addition, the library generates stunning visuals that you can share with customers or supervisors

What are you waiting for?

Give Klib a try and send a thank you to its creator Andreas Kenz 👉 https://lnkd.in/g4uwHCZM

𝗜 𝗽𝘂𝘁 𝘁𝗼𝗴𝗲𝘁𝗵𝗲𝗿 𝘁𝗵𝗲 𝘁𝘂𝘁𝗼𝗿𝗶𝗮𝗹 𝗜 𝘄𝗶𝘀𝗵 𝗜 𝗵𝗮𝗱 𝘄𝗵𝗲𝗻 𝘀𝘁𝗮𝗿𝘁𝗶𝗻𝗴 𝗺𝘆 𝗷𝗼𝘂𝗿𝗻𝗲𝘆 𝘄𝗶𝘁𝗵 𝗣𝗮𝗻𝗱𝗮𝘀

Designed for complete beginners, this tutorial will walk you through every function step-by-step, so you can make real progress using Pandas for data analysis

Even for the more experienced ones, this is a handy tool to have as it consolidates everything in one place. You can easily find what you need without sifting through dozens of tabs

Follow the link in the comments to make a copy - grab it now while it's still free! 


#dataanalysis #pandas #tutorial

𝗛𝗮𝘃𝗶𝗻𝗴 𝘁𝗿𝗼𝘂𝗯𝗹𝗲 𝗰𝗵𝗼𝗼𝘀𝗶𝗻𝗴 𝘁𝗵𝗲 𝗯𝗲𝘀𝘁 𝗮𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺 𝗳𝗼𝗿 𝘆𝗼𝘂𝗿 𝗺𝗮𝗰𝗵𝗶𝗻𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗽𝗿𝗼𝗯𝗹𝗲𝗺? 🤔

The Microsoft Machine Learning Algorithm Cheat Sheet has got you covered 

From classification to regression, clustering to recommendation systems, this cheat sheet will simplify your decision-making process

No more guesswork or second-guessing—check it out now!

#machinelearning #microsoft #cheatsheet

𝗔𝗿𝗲 𝘆𝗼𝘂 𝘀𝗼𝗹𝗲𝗹𝘆 𝗿𝗲𝗹𝘆𝗶𝗻𝗴 𝗼𝗻 𝗔/𝗕 𝘁𝗲𝘀𝘁𝗶𝗻𝗴 𝗳𝗼𝗿 𝘆𝗼𝘂𝗿 𝗲𝘅𝗽𝗲𝗿𝗶𝗺𝗲𝗻𝘁𝘀?

With 𝗠𝘂𝗹𝘁𝗶 𝗔𝗿𝗺𝗲𝗱 𝗕𝗮𝗻𝗱𝗶𝘁𝘀 you can take your experimentation design to the next level 

Here's how:

Traditional A/B testing, randomly assign users to one of two options and then compares which one performs better

MAB uses a more sophisticated approach that leverages a reinforcement learning algorithm to simultaneously test multiple variations of the system or “arms” over time

By dynamically adjusting the probability of choosing each arm based on the feedback received, MAB can quickly identify the best solution and continue to optimize it over time

This makes it a powerful technique to optimize the performance of dynamic systems, where the optimal solution changes over time

Traditional A/B testing may not be as effective in these cases since it only allows for the comparison of two options at a time and assumes that the optimal choice remains the same throughout the testing period

For example, in online advertising where user behavior and preferences change over time, MAB can be used to optimize ad placement by testing different options of ad copy, placement, and targeting parameters.

In data science, modeling is often considered the most glamorous aspect, but experimentation is far more common and useful. 

What proportion of your job involves experimentation versus modeling? 

#datascience #experimentation

𝟱 𝘆𝗲𝗮𝗿𝘀 𝗼𝗳 𝗿𝘂𝗻𝗻𝗶𝗻𝗴 𝗮 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗰𝗼𝗻𝘀𝘂𝗹𝘁𝗶𝗻𝗴 𝗮𝗻𝗱 𝗜 𝘀𝘁𝗶𝗹𝗹 𝗚𝗼𝗼𝗴𝗹𝗲 𝗳𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀 𝗱𝗮𝗶𝗹𝘆

Don't waste your time trying to remember intricate functions 

Instead, focus on understanding practical techniques that drive real business results

Nobody will pay you for remembering minutiae 

Think big picture and take control of your journey by investing in the skills that truly matter for achieving your goals

🔹🔸🔹

Did you know that I'm launching a newsletter? 
Don't miss out! Link to sign up in the comments 📩🔥

𝗛𝗼𝘄 𝗱𝗼 𝘆𝗼𝘂 𝘂𝗽𝘀𝗸𝗶𝗹𝗹 𝗶𝗻 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲?

Most data science resources are geared towards junior data scientists, with the vast majority of YouTube and Medium covering beginner-level content and toy projects

As you advance in your career, it becomes increasingly challenging to stay up-to-date. If you have some years of experience like me, I am sure you've asked yourself what's the best approach to upskill and stay ahead of the game 

One strategy that I've found effective to gain insights into how data science is applied in real-world scenarios is reading tech companies' engineering blogs

If you're looking to upskill beyond the basics, I highly recommend checking out the blogs below

I'm curious: what other strategies do you use to stay current with the latest developments in real-world data science?

#datascience #datascientists 

Tech companies' top  ML & DS Engineering blogs

Arthur C. Clarke was a visionary author who left an indelible mark on science fiction with his famous book "2001: A Space Odyssey," later adapted into a film by Stanley Kubrick. 

In this fascinating 1964 video, he makes prediction about the future of machine learning and brain-computer interfaces that are still relevant today.

One of the most memorable quote for me was: "I think we should regard as a privilege to be a stepping stone to higher things."

I'd love to hear your thoughts on this idea.

#machinelearning 


𝗧𝗵𝗲 𝗼𝗻𝗹𝘆 𝘄𝗮𝘆 𝘁𝗼 𝘀𝘁𝗲𝗲𝗿 𝗮 𝗰𝗮𝗿 𝗶𝘀 𝘁𝗼 𝗴𝗲𝘁 𝗶𝘁 𝗺𝗼𝘃𝗶𝗻𝗴

If you're thinking about learning data science, it's time to stop planning and start taking action

Waiting to craft the perfect plan it's an illusion that leads to endless procrastination

The only way to make real progress is taking action 

This isn't a feel good post, this is a wake-up call ⏰

I wasted 8 months of my life trying to come-up with the perfect plan to learn Python, which was totally useless

Only by starting you'll receive the real-life feedback to determine your next best move and finally lower your anxiety

Don't make the same mistake I did and start today!

#datascience #python #learning 

My coworker tenderly called it a data swamp 

#data

𝗙𝗿𝗲𝗲𝗹𝗮𝗻𝗰𝗶𝗻𝗴 𝗶𝘀 𝗮𝘄𝗲𝘀𝗼𝗺𝗲, 𝗯𝘂𝘁 𝗳𝗶𝗻𝗱𝗶𝗻𝗴 𝗰𝗹𝗶𝗲𝗻𝘁𝘀 𝗰𝗮𝗻 𝗯𝗲 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗶𝗻𝗴, 𝗲𝘀𝗽𝗲𝗰𝗶𝗮𝗹𝗹𝘆 𝘄𝗵𝗲𝗻 𝘀𝘁𝗮𝗿𝘁𝗶𝗻𝗴 𝗼𝘂𝘁

Check out this list of platforms to browse for work—link in the description!

- We Work Remotely
- Freelancer
- Wellfound
- Braintrust
- Upwork
- Toptal
- Guru

⭐  𝗔𝗻𝗱 𝗵𝗲𝗿𝗲'𝘀 𝗺𝘆 𝘁𝗼𝗽 𝘁𝗶𝗽

Explore the lesser-known, smaller job listing platforms. These hidden gems have less competition, making it easier for newcomers to land clients and establish a reputation.

Have you tried any of these platforms?
Or maybe you have other recommendations for finding clients as a freelancer?

#data #freelancing

👩‍💻The path to becoming a data scientist is difficult to navigate

With so many tools, notions and techniques to master, it feels overwhelming 🤕

This is where this roadmap comes in.

By breaking down data science into manageable chunks, it helps you master the concepts step-by-step, and build a strong foundation for your data career.

𝗟𝗲𝘁'𝘀 𝗱𝗼 𝘁𝗵𝗶𝘀 𝘁𝗼𝗴𝗲𝘁𝗵𝗲𝗿! 🚀

#datascientist #datascience #career

This might backfire, but I want to share a couple of options to keep using ChatGPT even if your employer has blocked it.


Option one: use one of the many open-source available, but be aware that the quality isn't at par with ChatGPT, and the risk of data leakage is real.

Option two (and my recommended one): use ChatGPT API. This only works if your employer has blocked access to the website or app and not the API itself.

Do you have any other ideas? 

The importance of Statistics for Data Science cannot be overstated

Yet, amidst of our analytical and modelling odyssey, we sometimes overlook the importance of revisiting the fundamentals

It's time to dust off our statistical toolkit by delving into 𝗳𝗶𝘃𝗲 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹 𝗰𝗼𝗻𝗰𝗲𝗽𝘁𝘀 every Data Scientist needs to master: 

1. Measures of Central Tendency
2. Measures of Concentration
3. Measures of Association
4. Measures of Dispersion
5. Measures of Symmetry

Are you ready? 

Let's dive in!

#datascience #datascientist #statistics 

Fundamental Statistical Concepts for Data Scientist

📢 𝗖𝗮𝗹𝗹𝗶𝗻𝗴 𝗮𝗹𝗹 𝗙𝗶𝗻𝘁𝗲𝗰𝗵 𝗲𝘅𝗽𝗲𝗿𝘁𝘀 𝗶𝗻 𝗺𝘆 𝗻𝗲𝘁𝘄𝗼𝗿𝗸!

🔎 If you've knowledge in the 𝗪𝗮𝗹𝗹𝗲𝘁 business model, let's connect!

Taplio

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