The existential need of Data scientists across multiple business verticals has grown radically by over 650% since 2012 as per the 2018 LinkedIn report.
Despite the pressing demands, only 35,000 people in the US possess the market appropriate data science skills.
While there are hundreds of giants who are incessantly hiring data science resources, there is a huge gap between the demand vs supply in the data science career path.
Following the sudden surge in the hiring activities of data science resources, a noticeable growth is expected to be witnessed in the salaries of data scientists in 2019.
According to the latest survey conducted by Burtch Works, while 82% of the surveyed organizations are planning to hire data science professionals in Q2 of 2019, the other 70% will be expanding their Data Science teams. There has been a massive surge in data science career path in India also.
With the volume of data the world is generating every day (2.5 quintillion bytes of data), a data scientist no less than a superhero.
What is a Data Scientist & what does the data science career path look like?
The Data scientist plays the role of a mathematician and computer scientist who helps identify the trending patterns from the volumes of data.
The career path in data science is the link between the IT and business world. He is the one who interprets the data generated by the business, performs computations on it to help the business develop a data-driven growth strategy.
What Data Science Roles are Out There?
The data science learning path has evolved significantly since 2012 and so has the data scientist’s role. There is an increased demand for professionals who understand the business, can work out a data-oriented framework and develop a solution based on it.
Based on the multiple tasks a data scientist has to cater to, the career path in data science has been broken down into below major profiles:
Business Intelligence Analyst (BI Analyst)
A BI analyst in the data science career path is the one who gets his hands dirty by dealing with the market data. His job is to identify the market and business trends and he achieves this by data-analysis.
BI developers play a critical role in developing business strategies by using customize BI analytical applications that the business users can interact with to understand the market patterns.
The Average Salary of a BI Analyst is $89,333 per annum
Data Mining Engineer
The role of data mining engineer is to analyze the organization’s data as well as identify the business trends for third-party organizations also. His role while pursuing a career path in data science extends into developing intelligent algorithms for further data analysis.
The Average Salary of a Data Mining Engineer is $95,429 per annum.
Data Architect
Data architects work to define the structure by working with users and system designers. His role in the data science career path is to make the data usable and accessible at an operational level without exposing it to any security risks.
The Average Salary of a Data Architect is $137,630 per annum
Data Scientist
Data science learning path involves playing the role of an interpreter who works to make algorithmic sense out of a business case. He is the one who develops hypotheses by understanding the business data and in the due course business patterns are explored.
They identify the trends as well as develop the solution framework to improvise a business strategy.
The Average Salary of a Data Scientist is $139,840 per annum.
Data Analyst
A data analyst manipulates the humungous data sets to make it suitable for processing at an organizational level. During his data science career path, he may be required to deal with the traffic data generated by a website or a campaign and change it to a format on which the business can work.
The Average Salary of a Data Analyst is $83,878 per annum.
Data Engineer
A data engineer during his data science career path in India or anywhere in the globe is required to process the gathered data in batch or online to make it readable enough for the data scientists.
The Average Salary of a Data Engineer $151,307 per annum
Check out the video to know more about the data science career path
Skills Should one Possess to Build a Career Path in Data Science
A data scientist is expected to possess heroic traits. During his data science learning path, he needs to be a proficient mathematician, a statistician, a program developer and must have strong analytical skills.
While the skill set for the data science career path seems too diverse, this is the reason why the data scientist’s rank 2nd on the most sought after profiles by organizations like Facebook, Oracle and more.
Technical skills conjoined with business understanding is must for a data scientist to drive the data-based strategies for the organization. Before we unbox the skill set let us look at the comprehensive responsibility list of the data scientist.
(i) Multi-Dimensional research needs to be conducted to frame the questions that need to be addressed
(ii) Extract relevant and volumes of data from multiple sources (both external and internal)
(iii) Develop and deploy sophisticated analytical algorithms that render machine learning capabilities to the programs.
(iv) Expansive use of the statistical methodology to prepare the data to be used optimally in predictive models
(v) Extraction of irrelevant data from the big data pools
(vi) Examine the relevant data from multiple business perspectives to identify the patterns and trends
(vii) Work-out solutions for the problems identified during data analysis
(viii) Development and maintenance of algorithms to solve existing problems
(ix) Translate the data into a more communicable form for the business users and IT developers.
Career path in data science requires coding skills, analytical skills, and statistical know-how and critically thinking is the arsenal for a data scientist career path. The industry trending skills for the data scientist are:
Programming Languages for Data Science Career Path
R, Python, Java, Scala, MATLAB and TensorFlow are few of the programming languages in which the data scientist is expected to be proficient.
Statistics and Applied Mathematics
The core concepts of statistics like descriptive statistics, hypothesis testing and regression are a must for a data scientist. Talking from the applied mathematics perspective, the person must have basic knowledge of linear algebra and calculus.
Server Data Segregation
As a data scientist one might have to send data across multiple servers due to memory issues. Hadoop is one of the most accepted platforms to convey data rapidly in real-time. Thus a basic knowledge of Hadoop is an added advantage.
Databases
A data scientist is incessantly communicating with the database that is why it is very important to have knowledge of SQL/NoSQL.
Writing queries to extract a different kind of data using SQL shortens the data access time and it takes to be the desired skill while pursuing a career path in data science.
Machine Learning and AI
Having a grasp of the machine learning and AI techniques like supervise machine learning, neural networks, Time series, deep neural networks, Outlier detection, Computer vision, Natural language processing, reinforcement learning, decision trees, Survival analysis, logistic regression, unsupervised machine learning, Recommendation engines, and Adversarial learning works in advantage of a data science career path in India.
The knowledge of ML and AI is important while pursuing the data science career path as the outcome is based on predictions and both ML and AI help build predictive models.
Data Visualization
The business world produces huge data without a break. To harness this data from a business standpoint, it needs to be easy to visualize for business users and IT developers.
Thus creating reports, charts, and graphs out of unstructured data are also very important skills while building a career path in data science.
There are multiple tools available like ggplot, Matplottlib and more that make data visualization easier. Using these tools converts the output of the data analysis into more representable formats so that they are easy to understand by the non-data-scientists.
Unstructured Data
The digital world is full of unstructured data that hold tremendous value for businesses. The Unstructured data holds both relevant and irrelevant data and it is the task of a data scientist to sort the data and convert it into structured data that can be propagated for use across the system.
The unstructured data is the most complex aspect of data science career path and requires critical thinking and that is why its analysis is called “dark analytics”
How to Build a Career in Data Science?
To build a career as a data scientist, one needs to put in some groundwork like understanding the job market needs, learning the appropriate skills and finding the right employers.
Below steps must be taken to stay on top of the best opportunities as a data scientist.
Before that have a look at what IBM has to say about the job market of Data scientists
Joining Data Scientist Social Groups
One needs to stay up-to-date about what is trending in the market and the best way to do that is to join groups over professional social media channels like LinkedIn.
Create a Github Account
Right! As you are moving a tech territory now, you must have a library where you can showcase your work to the job providers. It is a very important step towards a career as a data scientist.
Take a Data Science Course
We have learned mathematics, statistics, and programming at different walks of our career or studies but not from the perspective of data scientists. It is very important to enhance your skills the right way before you approach potential employers.
List Down the Target Role & Employers
It is critical to have a clear picture of what role and which organization you want to pursue a data science career path. Before you set out in the market with your profile, make sure you have the roles and employers in mind.
To wrap
Data science does not limit your growth to big IT giants, it is impressively spread out across the plethora of business verticals. Its demand is increasing uniformly and aggressively. So to be a successful data scientist one needs to work on the skills and the best opportunities just follow the right candidate.
If you are looking forward to doing a master’s in Data Science, have a look at these top institutes that provides Masters in Data Science.
To get the right data science skillset, you should enroll yourself in a Data Science Course. This will help you to elevate your career as a Data Scientist.
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