Five Steps to Advance Your Data Science Career (1)

Grow to your fullest in data science career (0)

No matter where you are now in your journey on doing data science, it’s always better to shorten your path and optimize your journey in values and happiness of a life. You should live a life in wholeness and reach your fullness both at work and after it. Life’s beauty lies on having a harmony between body and mind. With this philosophy in mind, I would like to share five steps to advance your data science career.

Step 0: Know why you take data science career

Before discussing the five steps to advance your data science career. I would like first to ask why you want to settle on a data science career. Many people follow the crowd, they chase a popular race because a career is in demand so it’s easier to find a job or it offers a higher pay. The why factor analysis is critical as it tells what motivates you and how far you can go and how much you can reach.

If you are following the crowd instead of your passion, you are chasing a race with less fun and end up with boredom. You may do it good, but you will never reach greatness in the career because you have no passion neither desire for what you do so you are not willing to put extra efforts on your career.?Desire is the best teacher and passion is the driver to success.?It’s well said?“Follow your passion, and success will follow you”

To become successful and reach to your fullest in the career, you should do self-evaluation first and make sure the career is well aligned with your natural passion and your calling in life.

>> how to find your passion and calling, please read the book?Grow to Your Fullest, four steps to stand above the crowd, bloom and bear fruits.

Step 1: Have a big picture and envision the end

Now suppose data science is what you love to do. The first step is to have a big picture and know the critical components of data science and AI , where you are now in the journey, where you want to end up.

It’s well said?that people without vision perish (Proverbs 29:18).?This applies to us both in life and career.?As a data science & AI professional, you must know what you want to become at the end or where you will be. And that should be part of your life vision, so you have a purpose and find meaning in career and have the passion to reach the best version of yourself.

Remember, always start the end in mind, draw a roadmap and chart your path on the journey. What do you think? please leave your comments and share your thoughts.

>> How do you get a big picture and your vision? Please read?Have A Big Picture and Envision the End

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Step 2: Build foundations for doing data science

Data science has been evolved from data analysis (Tukey 1962)?over about 60 years. Peter Naur first described data science in 1974,?The science of dealing with data, once they have been established, while the relation of the data to what they represent is delegated to other fields and sciences. Then it gradually becomes an interdisciplinary science. It incorporates principles, techniques, and methods from multiple existing academic disciplines and application domains.

According to Initiative for?Analytics and Data Science Standards,?Data Science consists of the two areas of foundational knowledge: Science and Math, Programming and Technology.

Science and Math includes basics of the scientific and research method,?hypothesis formulation and problem identification; machine learning methods (unsupervised, supervised, reinforcement and deep learning, etc.); statistics such as probability, inferential, stochastic processes and time series, causality, sampling; computer science such as data structures and algorithms, DB, OS, parallel computing, software engineering; and mathematics basics like calculus and linear algebra.

The second includes tools and technologies of designing, building, developing, controlling, operating, and deploying computational systems such as programming language, ML libraries, development environments, data visualization tools, database structure and cloud or big data platforms, etc.

To lay a solid foundation to advance your data science career, you should build the hard skills in the two areas. The list above includes a lot, but if you have a formal educational background in data science, the curriculum usually covers all the basic topics.

Given a data scientist grows by practice, based on your current knowledge base, you can start with a certain area of your focus like starting with machine learning algorithms if you have strong mathematic background or you begin with doing data engineering or developing data infrastructure if you have computer science background. If you do not have the two, but you know well the content and operations in a business domain, you can start with being a business strategist by leveraging the data. The basic idea is to start with something you are strong?then gradually develop relevant knowledge or skills.

How to create a roadmap? Read Build Data Science Winning Foundation?to get some guidance.

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Have different thoughts? Please leave your comments and share your thoughts.

In the next article, I will discuss Step 3 to Step 5.

May you grow to your fullest in your data science career!