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Where to chose, if I wanna be a Data Scientist?

How to Become a Data Scientist? #scientist #software #accounting #science #software-engineering #salary #technology

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Molly’s Answer

I would encourage you to look into the accounting industry! Firms are hiring more and more data scientists as we begin to use new ways to harness and bring big data to life for our clients.
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Abhinay’s Answer

Data Science courses are offered by many universities & colleges like IIITs, IIMs, Manipal institutes. Many engineering college have this subject as one of the optional in final year.

Data Scientist is the hottest job roles which is being seeked in the market today. All the domains like Banking, Insurance, Telecom, Aerospace, Retail, Utilities are using past & present data for analysis. These days every software company is spending resources & time for developing skills associated with Data Science. Every domain in IT industry wants Data Scientists & in fact they want business growth by investing heavily here. Specially if the question is regarding skills to be acquired for becoming Data Scientist then:

  1. Companies are using open standard scripting languages. Python application development skills are hot in market.
  2. Managing database especially big data like Hadoop
  3. Machine Learning & Artificial Intelligence
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Michael’s Answer

The good news is that there is an overwhelming demand for Data Scientists across multiple industries. From retail to accounting to private to public sector, there is a very strong need for data scientists and the demand continues to grow as companies and other organizations seek to find productive insightful ways to uncover meaning from their (and often time other's) complex data.

The journey to becoming a data scientist usually involves learning about data itself (the different kinds of structured and unstructured data), the methods for contextualizing of data (tagging it, categorizing, validating and understanding it) along with various methods (both mathematical and non-mathematical) for using / synthesizing the data to garner insights that drive an outcome or an understanding. For example, using data science to help a company recognize a previously unrecognized pattern that could warn them that a customer may leave their phone service and how to best incent them to stay... Or for an environmentalist org... If the fishing occurs in a certain area of the ocean, what can be the predicted effect on fish populations in other areas;-).

Any way you look at it, data science opens a world of opportunity and growth that truly is an interesting area to focus on and grow in (take a look at next steps and the links I've provided to learn more;-).

Here is an interesting link about how do actuarial and data science skills converge at insurers. - https://www.pwc.com/us/en/industries/insurance/library/actuarial-data-science-skills.html

Here is an interesting link that discusses not only data science, but the use of AI as well to help address environmental issues. - https://www.pwc.com/gx/en/news-room/docs/ai-for-the-earth.pdf

Michael recommends the following next steps:

TALK TO A DATA SCIENTIST... LOL... One of the best ways to understand a career path is to talk to someone who is doing it:-) Use your school to help you get in contact with one or you can query LinkedIn and kindly ask if they can spend a few minutes describing their career journey (who knows, you may score a great contact or future mentor)
You don't have to go to an Ivy League to become a data scientist. Also, you don't have to be a mathematical genius:-). That said, the opportunity for being a successful data scientist is not defined by just the school you attend or that you won a "Fields Metal." There are many areas of data science and data science adjacent careers to consider, so don't disqualify data science as a career too quickly;-)
Understand that data science is an interdisciplinary career path. More and more data scientists are using other capabilities such as AI and also industry acumen to become more effective, so make sure to be open to learning other disciplines and areas of study (both tech and industry)
Like in many scientific disciplines, the world of data science is ever evolving. Continuously look into the many different ways data scientists are used to establish a basis and direction for yourself.
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Sheila’s Answer

Hi Akira:

Data Scientist is one of the new hottest and upcoming careers today. A Data Scientist is someone who gathers and analyzes with the goal of reaching a conclusion.

How to Become a Data Scientist

There are three general steps to become a Data Scientist:

1) Earn a bachelor's degree in IT, computer science, math, physics, or another related field

2) Earn a master's degree in data or related field

3) Gain experience in the field you intend to work in (ex: healthcare, physics, business)

There are many paths to landing a career in data science, it is completely impossible to launch a career in the field without a college education. You will, at the very least, need a four-year bachelor's degree. Keep in mind, however, that 73% of the professionals working in the industry have a graduate degree and 38% have a PhD. If your goal is an advanced leadership position, you will have to earn either a master’s degree or doctorate.

Types of Degrees

Common degrees that help you learn data science include:

  • Computer Science
  • Statistics
  • Physics
  • Social Science
  • Mathematics
  • Applied Math
  • Economics

Salary

Glassdoor reports a salary average of $113,436 while PayScale has their earnings at $93,146. A data

scientist with 9 or more years of experience can expect a salary around $150,000 and those managing teams of ten or more can expect to earn close to $232,000.

The world of data science is always changing so you'll need to always update your skills. Here's a very good article to read on "how to become a data scientist". - - https://www.geteducated.com/careers/how-to-become-a-data-scientist

There are tons of big data in the world that could be analyzed by a data scientist. This career appears to be very lucrative and interesting. I wish you much success on your journey.

~ Sheila

Sheila recommends the following next steps:

Read the article on "how to become a data scientist" - - https://www.geteducated.com/careers/how-to-become-a-data-scientist
Thank you comment icon Shelia's response was fantastic. North Carolina State University offers a Masters in Data Science. Below is the link for additional details. https://www.csc.ncsu.edu/academics/graduate/degrees/ds.php Carmita Bass
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Vance’s Answer

TOP TIP: In an open-source world, don't wait on credentials or college course completions to get started. Download a package and a tutorial, find a data set that you are passionate about, explore. For me, I love sports, so pulling down NBA data excites me to spend hours digging in. Find a data set that you love. You can begin to build a resume as you learn.

TOOLS: Everyone uses different tools, so focus on the underlying impact and the sustainability of a language or tool if you are going to invest your time there. If I had to choose, I'd start here:

  1. SQL
  2. Python
  3. R
  4. Tableau

FREE: Find online courses and dig in. Build models. When employers hire in this space, having a tangible portfolio in this space that you can speak to in-depth is every bit as powerful as an expensive degree from a major university.

As you know, "Data Scientist" is a broad bucket, and can mean one skill or a combination of several skills. I'm a fan of first making sure you know WHY you want to be a data scientist, and letting that guide your path. Be clear about the types of problems that you are passionate about solving. If that requires data acquisition skills, start there. If it requires intense statistical analysis, focus your research there. Other work may be more frontend or data visualization, and that would help inform you about where to start too.

Vance recommends the following next steps:

Learn to build models, document your work, and prove to yourself that you can solve complex problems.
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Archived’s Answer

Hi Akira! There are some great answers already; here are some of my thoughts. Data science in business is all about making decisions - whether it's making better decisions, or making good decisions faster. To get practice in this, you could identify a field that you are very interested in -- that you know a lot about -- and where there is plenty of data. Depending on your interests, there are many publicly available datasets to find. Start thinking about the kinds of decisions that people in this field need to make. What outcomes do these decisions affect (winning games, increase in sales, decrease in illness, etc.)? What data could support those decisions? Can you use the data you have to predict the decisions that people are actually making? Can you use the data to predict the outcomes of those decisions? As you start to delve into this, you may realize you are missing a skill that you need in order to move forward. That's great - you can set out to learn this skill, now with a purpose in mind. Share your findings (and the thinking that brought you there) with others, find out what they can contribute. What questions do they ask? Does that make you realize there is something else you need to learn?

Archived recommends the following next steps:

Explore the decisions people are making in a field that you are passionate about.
Start trying to support or automate these decisions (you can do this on your own, as a simulation).
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