The career as a data scientist has evolved fundamentally over the last few years. A decade ago, Forbes had predicted that a data scientist’s job would be the hottest job, and now we are witnessing it.
Some of the best career opportunities now and in the foreseeable future are in the field of big data and data science. LinkedIn put data science on number 12 and 23 on the list of skills companies would need in 2019.
The high demand is mainly due to the huge amount of data generated by the online activities of the users. What is also exciting about the career is a diverse background of the professionals from the field of Physics, Mathematics, Statistics, and Computing.
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Is Data Science a Good Career Option?
The career as a data scientist guarantees huge paychecks, meaning it’s a good profession consider. With the growing power of the internet, everyone wants to be an IoT pro, a data scientist or an AI Engineer, with expanding web the scope of data science is also growing and that too at a very high speed.
The new internet technology and big data is here to stay, and that means the demand for data scientists will continue to grow in the future. An advanced degree like Masters of Data Science can improve your earning potential and broaden career pathways in this field. Some of the prominent Data Scientist job titles are:
- Data Scientist
- Data Architect
- Data Administrator
- Data Analyst
- Business Analyst
- Data/Analytics Manager
- Business Intelligence Manager
What Skills Are Needed to be a Data Scientist?
It begins with your graduation. Earning a bachelor’s degree in IT, Mathematics, Physics, Computer Science or another scientific field where your learning evolves around coding or data crunching is the first step. Then you earn a master degree in Big Data, AI or Machine Learning and gain professional experience in the field you want to acquire expertise in.
Data scientists use analytical skills to sort and analyze data and then visualize it using software such as Tableau that can help businesses take a data-oriented decision.
How To Do Self Study If You Want To Be A Data Scientist
Let me break the truth to you. Data Scientist might be the suggestive job of the 21st century, but it’s not everybody’s cup of tea. To set your career in this field you do not just need to acquire some technical skills but you must also have a good knowledge of where and how to apply those skills. This understanding comes with working and studying on varied data-sets and applying your skills on them.
Even a PhD level physicist or coder needs a great time to understands the nuances of big data, machine learning, how the industry can benefit from that data and how can he use this data to save the industry from pitfalls.
You can get yourself enrolled for the online Big Data courses that are usually 2-3 months long and also offer a certification. To dive deeper into Big Data such as Scala, Apache Spark you can use the Cloud Labs offered by online tutorial portals. Some tech giants like IBM and Microsoft offer chances to join their programs as the intern or team assistant where you can gain the practical experience by assisting the master scientists that too sitting at your home.
How to Launch Your Data Science Career
Data science is an interdisciplinary field, and its definition is constantly changing. Becoming a data scientist requires both quantitative and analytical skills, as well as knowledge of programming languages, databases, and visualization and reporting big data. According to LinkedIn, the skills most in demand for data scientists right now include data analysis, statistics, machine learning, Python and SQL. Soft skills like communication, business savvy, creativity and networking are also assets.
- The first step in becoming a data scientist is to have an interest in and aptitude for maths, statistics and machine learning. Many IT professionals can enhance their competencies to gain the skills and capabilities needed for a career in data science.
- Next, you need to acquire the technical skills necessary, including coding, databases, and visualization and reporting data. The best way to acquire the necessary combination of skills is to complete a masters of data science program. You don’t need to go to a university to become a data scientist, you can start by watching some YouTube tutorials and get your hands dirty analyzing datasets available online. Kaggle is a good website to download datasets for practice. Once you realize this is something you will be interested in, you can opt for a online masters data science program to enhance your skills.
- To find a job in the field of data science, you need hands-on experience that you can put in a portfolio for prospective employers. Internship is a good way to get to gain some practical skills.
Meet other data scientists and network: Whether it’s participation in group projects, seeking out a mentor, or attending conferences and presentations, networking with other data scientists can help you gain experience, develop the field and open up new career opportunities.
- Get business savvy: Data scientists need to have a keen sense of how their analytical insights can help businesses to perform better and to meet their desired outcomes.
- Work on the soft skills: As well as technical skills and analytical ability, data scientists need the so-called soft skills like communication, creativity, curiosity, skepticism and even humility. And above all, a hunger for more data.
What is a Data Scientist Salary?
The recent Glassdoor report opines that the pack for the best jobs in the US and around the rest of the world is led and dominated by the Data Scientists. The median salary for this highly hyped job is a huge $116,000 and with more than 1,956 job openings posted on the portal it also tops the median of career index.
The average salaries of the job openings as a Data Scientist on indeed are 114% higher than the average paychecks for all other job postings on the site.
How To Become A Data Scientist While Pursuing Another job
Those who aspire to make a transition to Big Data career can access many online resources with a little or no money. But it takes a huge level of commitment and time to follow through as this field is still evolving and no “crash course” can make you an expert.
For self-starters MOOCs (Massive Open Online Courses) and Coursera are ideal platforms. The flexible scheduling will allow you to watch and understand the lecture after you get back from the office. Also, you can complete your assignments at anytime while commuting or in your leisure time. But the thing is the lack of student-teacher or peer-to-peer interactions needs you to follow the discipline if you really want to utilize your time.
There are a lot more courses and online resources, data-sets, cloud labs available now than it used to be 3-5 years ago. The quality of the courses can be a little tough to judge as you begin, but be assured there are definitely many helps out there, so long as you are willing to follow the commitment and discipline to master it!! Good luck!