Learn from the Industry Experts and Professionals to grow a Career in Data Science

By POOJA BISHT |Email | May 31, 2019 | 1401 Views

You may have learned about the top skills of Data Scientists through various blogs, but learning from an expert is the one thing that you should do now. In this article, we will not write about the long list of the tops skills possessed by a Data Scientists as most of the bloggers do but will focus on entirely telling you what the professionals think about the role of a Data Scientist. The article contains the YouTube videos of these Professionals' talks which you must see to know the relevant things about the Data Scientist role. Some of the Professionals are also Data Scientists while others are Experts having in-depth knowledge about the field.
This talk by Jose Miguel Cansado focuses on how big data starts to drive the world, and what kind of skills will you need to interpret it? Jose Miguel Cansado is the General Director of Alto Data Analytics and has developed his international career in IBM Watson and Alcatel-Lucent, including eight years in Pacific Asia as Head of Multimedia and Mobile Communications. The talk was given at a TEDx event and is very knowledgeable for the beginners and professionals in Data Science.

In this video, Dr. Goutam Chakraborty of Oklahoma State University explains the top skills you need to be successful as a data scientist. The skills which he focuses on the video are:
  1. Programming Skills
  2. Data management skills
  3. Statistical skills
  4. Mathematical and programming skills
  5. Communication skills
You should look at the video to know the reasons he put forward on mentioning these skills. Maybe you already know the importance of these skills but when you hear from an expert, a sort of clarity reflects. The video is short, so it won't take much of your time as well.

Michael is a data scientist at Google and is from a Ph.D. in Physics Background. There is a myth surrounding the people regarding the qualifications possessed by a Data Scientist. People think that only a Ph.D. In computer science can become a Data Scientist which you will break in this video. You will learn the experiences of Michael about his journey from Mercedes (Previous Company where Michael work) to Google. Google is the dream place to work for every data scientist. You will also get to know about the Google interview . This will help you in knowing the hiring process of a data scientist in Google, which you can easily take advantage of in your future interviews with Google (if you do). 
The interview also revolves around some of the very important questions like:
  1. How do you develop a knack for data wrangling?
  2. How do you approach a problem that has multiple solutions? 
  3. How important is SQL compared to python in 2019?

This is a talk with Mansha, a data scientist at Instagram. Mansha explains what exactly data science is for her. Listen to this talk to get the answers to the most important questions about working as a Data Scientist and the interview process for it. Data Scientist community, especially Women, who want to develop a career in Data Science and aspiring for Data Scientist will be inspired by this video. Some of the questions asked in the interview are:
  1. How did you become a data scientist? 
  2. What does your day to day look like? 
  3. What kinds of people become data scientists? ## Most important for you.
  4. What does the interview process look like? 
  5. What should a candidate bring to a job interview? 
  6. What's it like to be a woman in data science? #Perfectly for women.
In this video, Imran shares his experiences while working as a Data Scientist and leading a team. He explains the various software he uses as a Data Scientist. You can gather the learning about the opportunities that a Data Scientist need to handle. The opportunities could little vary from other companies but it will give an overview of the Data Scientist role. You will get to know "what exactly does the Data Scientist do?" in the video.

Recommended for you: Lessons Learned the Hard Way: Hacking the Data Science Interview

Source: HOB