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Data Scientist: Career Path

There is a global shortage of data scientists in the industry! Enter the world of stats, maths and data & bring valuable insights to the world's top corporations!

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What does the Data Scientist career path entail?

Data Scientist

Data Scientists are more in-demand than ever! While many folks in the data space try to get their hands dirty with AI and Machine Learning, they are leaving a big gap in the job market for data analysts and scientists.

In the US today, over 3,000 new job postings for Data Scientists are found. The space is growing and getting more open for career changers.

A Data Scientist can expect to be among the top range of tech salaries. Well into the six-figures in the US on average, and at top ranges all around the world!

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Best books to explore the Data Science career path.

A well-written and thorough book can be an amazing path to build deeper understanding and also act as a handbook as you discover the internet's vast resources.

These are our and our experts top picks to get started building career-relevant skills.

Python Data Science Handbook

Python Data Science Handbook

For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.

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Introduction to Statistical learning

Introduction to Statistical learning

ISL is a fundamental book and popular amongst undergrad and grad students for its clarity and simplicity with explaining concepts. The math required to understand the book is kept to a minimum, making it unique in its format.

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Head First Statistics

Head First Statistics

Whether you're a student, a professional, or just curious about statistical analysis, Head First's brain-friendly formula helps you get a firm grasp of statistics so you can understand key points and actually use them. Learn to present data visually with charts and plots; discover the difference between taking the average with mean, median, and mode, and why it's important; learn how to calculate probability and expectation; and much more.

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R for Data Science

R for Data Science

This book will teach you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it. In this book, you will find a practicum of skills for data science.

Just as a chemist learns how to clean test tubes and stock a lab, you’ll learn how to clean data and draw plots—and many other things besides.

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Statistics for Data Scientists

Statistics for Data Scientists

Statistical methods are a key part of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.

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Courses to deepen your Data Science skills.

These days, courses are no longer a sequence of videos. They are usually accompanied by projects and a learning community, keeping you accountable and on the path.

Our experts recommend these courses, from free selections to paid programs.

Fast.ai

Fast.ai

With the motto "making neural nets uncool again", fast.ai is a straight-to-the-point practical (and free!) course that is valued by Machine Learning enthusiasts and engineers worldwide. Fast.ai comes with a community, many practical projects and great content.

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MIT Open: Linear Algebra

MIT Open: Linear Algebra

Math is the foundation of Machine Learning and much needed if you need to work on the inner logic of its systems. Senior engineers are encouraged to propose and submit their own papers – and getting your LinAlg back in order is a must for that.

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Data Science A-Z

Data Science A-Z

Learn Data Science step by step through real Analytics examples. Data Mining, Modeling, Tableau Visualization and more!

Successfully perform all steps in a complex Data Science project, read statistical software output for created models and receive professional step-by-step coaching in the space of Data Science

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Harvard Online Data Science

Harvard Online Data Science

To become an expert data scientist you need practice and experience. By completing this course you will get an opportunity to apply and gain knowledge in R data analysis. This final project will test your skills in data visualization, probability, inference and modeling, data wrangling, data organization, regression, and machine learning.

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Machine Learning A-Z™

Machine Learning A-Z™

Kirill Eremenko's course on Udemy is a classic with almost a million (!) students worldwide. A-Z takes you from a bit of coding knowledge to making your own predictions and building ML models pretty swiftly. At prices between $10 - $20 it's also cheaper than many alternatives.

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Lex Fridman's MIT Deep Learning

Lex Fridman's MIT Deep Learning

Lex Fridman is the instructor of an immensely popular and fundamental Deep Learning course at MIT. Together with the other MIT AI courses, this can help polish your skills and get the foundations right.

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Get the guidance you need on the Data Scientist career path

There is no better source of accountability and motivation than having a personal mentor. What used to be impossible to find is now just two clicks away! All mentors are vetted & hands-on!

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Linda Oranya 🇱🇹

Data Scientist at .
5.0 (10)

I am a data scientist with experience in creating insights from data, making analyses, building predictive models. I love to impact while getting impacted on. I look forward to building a community of data-aware individuals and communities who would use data to solve the unique problems of their community.
Engineering & Data Python SQL Data Science Machine Learning PowerBI Data Visualization
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Jaret Andre 🇺🇸

Data Science Mentor (Full-time) | Ex Data Scientist (MLOps)
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WHY DO I WANT TO BE A MENTOR? Feeling not good enough? Don't think you are fit to be in the data science industry? Feeling lonely, stressed or even depressed? Wondering why you can't break into the industry? Wondering why no one is taking a chance on you? Considering additional …
Engineering & Data Data Science MLOps Machine Learning Statistics Software Engineering Goal Planning
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Govind Malhotra 🇬🇧

Principal Data Scientist at Consulting
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Govind has been working in data science consulting industry for 9+ years and has solved industry problems through building scalable machine learning solutions across multiple domains :- Insurance, banking, telecom and healthcare. He has helped mentees landing their first data science jobs or transition into new roles.
Engineering & Data Machine Learning Statistics Data Science Python Deep Learning SQL
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David Lara Arango Ph.D 🇳🇴

Chief Data Scientist | Top 4% mentor | AI-Data-Cloud-Software Engineer | Expert advisor | 65+ successful mentorship cases in various platforms
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--------------------------------May DISCOUNT--------------------------------- All my programs will have a 25% discount until May 31st. This discount can also be used in conjunction with the quarterly discounts :) --------------------------------May DISCOUNT--------------------------------- Hi there! I am multilingual Chief Data Scientist/ML-Data and Software Engineer with over 12 years of experience in data science, data analytics, …
Engineering & Data Artificial Intelligence AI Data Science Data Engineering Data Strategy Cloud
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Ilya Tyutin 🇨🇾

Value-centric Data Scientist
5.0 (1)

Please note: If the technology side of Data Science is your main interest, please consider connecting with other talented individuals on the platform. I can help you to become a strategic partner instead of someone that needs to be managed. Do any of the below statements ring true to you? …
Engineering & Data Data Strategy Data Science AI Strategy AI Opportunity Discovery AI Development Dysfunctions Data Products
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Leoson Hoay 🇺🇸

Data Scientist at Learning Collider
5.0 (27)

Hello there! I am a Data Scientist at Learning Collider, previously Tech Lead at the University of Chicago Urban Labs. I have always been passionate about leveraging technology to solve human problems, and have many years of experience in hiring for data teams, and extensive programming and statistical knowledge. I …
Engineering & Data Data Science Python Machine Learning Technology Management Data Scientist Data Analyst
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The Data Science must-reads you shouldn't miss.

Key articles and posts of industry experts can help you get a better picture of what you are getting into.

In our opinion, these are some must-reads you really shouldn't miss.

Simple Reinforcement Learning with Tensorflow

This 8-part series by Arthur Juliani (Deep RL researcher at Unity) is an amazing entry point to the new and mysterious advancements of Reinforcement Learning, perfectly suited for folks coming from other topics in Machine Learning.

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Karpathy on "Software 2.0"

Andrej Karpathy is the Director of AI at Tesla. Before that, though, he authored this blog post in 2017 talking about Deep Learning as "Software 2.0" of some sort. A must-read if you ever want to have another way of thinking about ML.

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Opportunities and projects in the Data Science space.

In the end, advancing your career is all about getting the right opportunities at the right time and a good portion of luck.

These are some interesting things going on in the Data Science space and you probably don't want to miss them.

Specialize with Kaggle

It wouldn't be the first time I've seen someone get hired over good Kaggle results! Kaggle competitions are data science and ML projects that are graded through a public leaderboard. A good place on the leaderboard shows that you know your craft and can apply your knowledge to real-life problems!

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Get into open-source

The world thrives on open-source software and this is no exception. Core contributors to core libraries and fast-growing tech like React, scikit-learn, Bitcoin and TensorFlow prove their abilities by going into the inner workings of a framework to improve it. For many companies, that's a desirable skill!

These projects are always looking for fresh faces. Grab an issue from the issue board or review a PR to get started!

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Growing into a Senior Data Scientist role pays off – $20,000 up to per year.

Not only is the progression from individual Data Scientist to a Senior role a natural progression, it also makes all the difference in your average salary.

On a global average, Senior Data Scientist receive a $20,000 salary hike over entry-level Data Scientists when they go from individual contributor to senior personnel.

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Related career paths

If you like Data Science careers, you might also be interested in these other career paths.

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