Getting a Data Science Interview: Resumes & ATS & More

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Victor Palacios

1:23:36

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1. Introduction

1.1 Udemy Relevant Links.pdf

1. Introduction.mp4

02:24

2. Data Titles & Common Misconceptions

1. Data Titles & Common Misconceptions.mp4

16:03

3. Getting an Interview

1. Expectations.mp4

10:50

2. Applicant Tracking System.mp4

09:23

3. Resume.mp4

17:15

4. Resume Review.html

5. Linkedin.mp4

12:14

4. Wrapping It Up

1. Goals and Tracking.mp4

03:42

2. Requirements.mp4

03:09

3. Improving Odds.mp4

04:43

4. Last Remarks.mp4

03:53

Description

The no-BS course to help increase your chances of getting a data interview using real data from over 100 data scientists

What You'll Learn?

Get a recruiter to call you back
Understand the impact and malleability of data science job titles on call backs
Write a resume optimized for data science Application Tracking Systems (ATS)
Use targeted strategies on Linkedin for getting a data science interview
Recall critical facts about job hunting including timing, length, and psychology

Who is this for?

Data Scientists, Machine Learning Engineers, Data Engineers, Data Analysts, and so on trying to get a data role interview.

What You Need to Know?

No previous experience required

More details

Description
My Primary Objectives in the course will be to:
Increase the number of call backs you get for data-related roles
Explain the role of data job titles for an application tracking system (ATS) and a human recruiter
Provide an understanding of how an application tracking system (ATS) ranks data-related resumes
Show specific examples of bad and good data-role-seeking resumes
Demonstrate specific LinkedIn strategies for getting a job which I provide evidence for
My Secondary Objectives:
Give you a firsthand look at the psychology of the recruiter
Set expectations appropriately for each task in the job hunting process
Look at ways around the ATS system (i.e., strategies for targeting humans directly)
Create a fun learning environment
We will be tackling all of these using data from over 100 data scientists as well anecdotal and personal data from my own job hunting experiences. This course has taken me 2 years worth of research to create and the feedback I receive is always that there is something new to learn even from veterans in the data field. While you may be an excellent data scientist, engineer, etc. you may not know the best strategies for landing interview which is half the battle.
Who this course is for:
Data Scientists, Machine Learning Engineers, Data Engineers, Data Analysts, and so on trying to get a data role interview.

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Data Science

Victor Palacios

Instructor's Courses

Background: Victor received his master's degree in data science from the University of San Francisco and is currently working in the same field at the University of San Francisco as the Director of Data Science Partnerships. He teaches and mentors courses on data science, machine learning, and Python. His initial projects and interests were in the deception detection space and health care. Victor has over 4 years of experience in the data science space.Education: University of San Francisco, MS in Data Science, 2021 Nagoya University, MS in Information Science, 2015 UC Berkeley, BA in Japanese, 2011Interests: NLP and LLMs

Udemy

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Students take courses primarily to improve job-related skills.Some courses generate credit toward technical certification. Udemy has made a special effort to attract corporate trainers seeking to create coursework for employees of their company.