Data Scientist: The Sexiest Job of the 21st Century
By: Qasim Hassan
Tags: Skills For 21st Century, Data Science, Artificalintelligence, Career Advice, Fundamental Duties

Fig 1.1 Shows Analysis work of a data scientist

Who is Data Scientist?

Ever wondered how to become a data scientist? Also known as the Data Science Unicorn, a data scientist offers an unmatched blend of skills, much to the satisfaction of their employer. Data scientists not only understand the language of data, but they can also analyze it and draw actionable insights from it. Moreover, they’ve mastered the art of data storytelling to a level that makes both management and stakeholders nod in agreement and plan their strategy accordingly.

What does a data scientist do?

Practically everything. Data scientists have a strong curiosity and a passion for achieving practical business impact. In addition, they boast exceptional judgment combined with an analytical mindset. But what sets apart the best from the rest is a knack for creative problem solving and willingness to learn new technologies and skills. Why is that so important? Because data scientists must use machine learning models to solve challenging problems in all business areas. Moreover, they are real champions in utilizing statistical natural language processing to mine unstructured data and extract insights. Which doesn’t mean they don’t also deal with structured data. In fact, it’s quite the contrary. Data scientists model structured data with advanced statistical methods and algorithms to perform analyses. Then, they interpret the results and visualize the data to tell the most compelling stories to management and stakeholders to achieve the company’s business goals.

How much does a data scientist earn?

How much do data scientists make? Here are the numbers, according to Glassdoor and PayScale. As a data scientist in the U.S., even with zero experience, you can get a $10,000 annual bonus on top of your $100,000 average annual pay. And, just in a few years’ time, your earnings can increase to $118,000, plus $12,000 in bonuses! You’ve set your gaze to London’s Big Ben and the UK? With no previous experience as a data scientist, you can expect to earn an average total compensation of £33,813. And once you have 1–4 years behind your back, your average total compensation will rise to £39,573. Overall, the data scientist career outlook is undeniably positive. No wonder “data scientist” was coined the sexiest job out there!

What’s the data scientist career path?

You can start as a business intelligence analyst or data architect or data analysts, and gradually work your way up to this coveted job. In any case, if you’re aiming at the data scientist position, here’s everything you need to know to get started on the right career track.

How to become a data scientist?

Fig 1.2 Arise a question who can become a data scientist?

Everybody wants to know how to be a data scientist. Well, maybe not literally everybody, but this is undeniably the most sought-after career in the data science field at the moment, as the demand for data scientists is constantly growing. Data scientists are independent and impactful, and If you want to get hired as one, you’re probably wondering what the data scientist duties are, how to acquire the necessary skills to apply for data scientist positions, and if the salary will meet your expectations. Is a data scientist a good career? To save you browsing through job boards and career websites to find the various information you need, we created this ‘data scientist snapshot’. We believe it will give you the insights you need to decide if the data scientist role fits your career needs and aspirations.

What education do you need to become a data scientist?

For starters, you don’t need a Master’s or a Ph.D. degree to become a data scientist. If you already have it — great! It’s certainly a plus! However, a Bachelor’s degree is good enough to get you on the data scientist path. According to our extensive research on how to be a data scientist, a background in the following disciplines increases your chances of landing a data scientist job:

Economics and social sciences, which includes economics, finance, business studies, politics, psychology, philosophy, history, and marketing and management;

Natural science, including physics, chemistry, and biology;

Statistics and mathematics;

Computer science;

Engineering;

Data science and analysis, which includes machine learning.

The good news is that even students from entirely different areas of studies, hold a very good chance of becoming data scientists. According to data from successful data scientists’ LinkedIn profiles, 43% have completed at least one data science online course with 3 certificates being the average. So, if you’ve never written a line of code in your life, you can still make up for it with determination and commitment to learning… And ultimately start a career in data science.

What data scientist qualifications you should acquire?

Data scientists are famous for their robust skillset and competencies. So, here are the must-have qualifications you need to become a data scientist. But how can a single person be outstanding in the technical domain, business acumen, and interpersonal communication simultaneously? Well, it’s all about acquiring the right skills

Technical skills

• Excellent programming skills in R or Python and its data science libraries (Pandas, sci-kit-learn);

• Experience with relational databases and SQL;

• Experience in MATLAB;

• Advanced practical knowledge of data science and machine learning /AI development frameworks;

• Excellent analytical and learning skills;

• Experience in Deep Learning frameworks (e.g. TensorFlow);

• Experience with NLP algorithms is an advantage.

Practical skills

• Ability to start initiatives;

• Integrity and confidentiality;

• Desire to drive innovation and generate unique solutions;

• Growth mindset;

• Ability to track and share external trends, best practices or ideas;

• Drive for performance;

• Accountability;

• Ability to thrive under pressure and fast pace;

• Ability to take an unpopular stance

Soft skills

• Strong written and verbal communication skills

• Leadership skills;

Conclusion