Career in Data Science. Why it is booming fast?
Starting the trending topic like CAREER IN DATA SCIENCE with a JOKE might not be the best decision here. Still, let’s have it,
“The data science motto: If at first, you don’t succeed; call it version 1.0”.
- Why Choose Data Science As A Career?
- It is all about the Data
- Industrial Applications Of Data Science
- Why is Data Important?
- How can I start my career in data science?
- Understanding of Data
- Logic & Algorithms
- Data Science Career Options
- “THE SEXIEST JOB OF THE 21ST CENTURY”.
- Data Scientist
- Data Warehouse Architect
- Data Analyst
- Data Mining Engineer
- Machine Learning Engineer
- Business Intelligence Developer
- Industry-wise options for Data Science Career
- Data Science Salaries With Various Profiles
Why Choose Data Science As A Career?
Data Science is an extremely popular topic. It opens several career paths which have huge demand today. So, if you decide to walk this path, you must know:
- Where to start?
- What is required and expected of you?
- What you need to be good at to work alone as a freelancer?
In this detailed blog on Career in Data Science, we will be focussing on your development as a Data Scientist, Data Analyst, Data Miner and more.
It is all about the Data
DATA. It is all about data. The amount of data produced every day is mind-boggling: 2.5 quintillion bytes. So, the person who is responsible for handling and maintaining the data is truly a HERO. That is why BIG DATA is considered as the best career option.
Industrial Applications Of Data Science
Furthermore, Data science has many applications in various industries. Hence, Data science professionals and experts are needed in multiple fields. As there are multiple options to choose from, DILEMMA is surely there. So, you might wonder, which is the best for you?
Data Science has grown hugely. It has gotten divided into multiple subsets such as:
- Data analysis
- Predictive analytics
- Data mining
- Business intelligence
- Machine learning
- Deep learning
This subsets of Data Science are individual career options for you. Also, data science is not going anywhere. It is growing rapidly every day. Furthermore, if we talk about its benefits, there is no industry which cannot benefit from it.
- Retail and e-commerce,
- Logistics and transportation,
- Real estate
Why is Data Important?
Everyone has and needs data to grow their business. So, to generate tangible data is what requires smart Data Science personnel. This is where a career in Data Science can prove worthy for you.
Data Science personnel is responsible for decision making study. So, you need to be smart enough to predict the scenario and offer a solution. So, it is not as easy as it looks like.
How can I start my career in data science?
This is a question troubling many newbies. To get started for your career in Data Science, you need to master the following things:
Python is typically the most common language required for Data Science career roles. It is also a versatile language with several libraries to assist.
So, it can be used for almost all steps involved in Data Science. It allows you to create data sets. It helps you in quantitative and analytical computing.
You also need to know conditions, loops, Database, API, deployment, variables, constants etc.
Understanding of Data
Data Science is a combination of various disciplines. They focus on analyzing the data and finding the best solutions. Previously it was done by Mathematicians and Statistical analysts. Then this turned to AI & ML and became extremely popular.
So, it’s all about encompassing the large available data into a human-readable format. Then using it to solve the existing problems.
Common processes involved here are:
- Collecting raw data on a server.
- Label the observations.
- Data cleansing, balancing & shuffling.
Logic & Algorithms
Programming is all about LOGIC. Unless you have good critical thinking & a strong hand on logic, you will not succeed.
What is an Algorithm? It is simply a set of instructions given to a computer to perform a specific task.
You have to understand, how the algorithm functions or processes. If you succeed, BINGO, you have developed a good hand on logic.
Data Science Career Options
It is a fact that there are millions of job openings for Data Science professionals. Is has been labelled as,
“THE SEXIEST JOB OF THE 21ST CENTURY”.
Again, every BIG corporate need Data Scientists to stay ahead of their competitors. How? By using insights provided by Data Scientists explicitly related to customer behaviour and preferences.
Companies like Apple, Microsoft, Oracle, Walmart have regular openings for this profile.
Some of the following statistics might interest you more.
- 2018: India’s demand for Data Science professionals rose by 417%.
- 2019: 2.9 million Data Science job openings were required.
- 2020: Demand may rise up to 2,720,000.
According to U.S. Bureau of Labour Statistics, 11.5 million news jobs will be created by 2026.
Data Scientist is an analytical expert who utilizes his knowledge and skills to find trends, patterns and manages data.
They have a huge responsibility for analysing, processing data. Then provide actionable plans for the organizations to grow their business.
So, it is a huge responsibility considering its intensity only. They help in finding solutions to business challenges.
- Understanding of supervised and unsupervised machine learning methods.
- Data related programming skills in Python or R.
- Familiarity with Apache spark.
- Ability to evaluate statistical models.
Data Warehouse Architect
A data architect is a practitioner of data architecture. Additionally, it is a data management discipline concerned with designing, creating, deploying and managing an organization’s data architecture. Data Architect is the in-charge of the company’s data storage system.
- SQL skills.
- Data management knowledge.
- MSSQL server.
Data Analyst works with IT teams, the management or Data Scientists to determine organizational goals. They are responsible for mining and cleaning data from primary and secondary sources then analyze.
And finally, interpret results using standard statistical tools and techniques. For example, a recent marketing campaign can be analysed for performance and weaknesses.
- Mathematical ability.
- Python & SQL.
- Ability to analyse a model and interpret data.
- Logical approach.
Data Mining Engineer
Data mining engineers deal with generate data for a business. It may be for your own employer or a third party. Data mining is basically a process of discovering patterns.
Also, it covers examining existing data to generate a piece of new information. This process uses software to look for patterns in large batches of data. It helps in understanding more about customers, thus helping in creating effective marketing strategies.
- Familiarity with data analysis tools, especially SQL, NoSQL, SAS, and Hadoop.
- Experience or knowledge of Linux.
- Big data processing frameworks.
- Basic statistical knowledge.
Machine Learning Engineer
Machine learning engineers are programmers focussing on programming machines to perform a specific task. They create programs to enable machines tack actions without being specifically directed to do so.
- Applied mathematics.
- Data modelling and evaluation.
- Signal processing techniques.
- Natural language processing.
Business Intelligence Developer
Business Intelligence Developers uses software tools to transform data into useful insights that influence business decisions. Additionally, they access, analyse and present analytical findings in reports, summaries, charts, graphs etc.
- Experience with BI tools.
- SQL/NoSQL queries.
- Data warehouse design.
- Technical documentation for BI tools.
Statisticians work to improve a single, simple model to best fit the data. Also, they tend to focus more on quantifying uncertainty involved in the data processing. Furthermore, they use techniques of numeric and quantitative analysis.
- Statistical terms and concepts.
- Analytical skills.
- Mathematical ability.
Industry-wise options for Data Science Career
Cyber Security: Data science can help build impassable protocols. With the help of effective Analytics, Data Science can enhance the cybersecurity industry. Also, your generated data of previous attacks can help you prevent future threats.
Healthcare: Medical imaging, the biggest use of Data Science in Healthcare. We can teach computers to interpret MRIs, X-Rays and other images and identify patterns for future help. Additionally, this can help in identifying tumours, anomalies and various other factors.
Agriculture: Data Science can assist agriculture by means of field monitoring via satellites. Also, prediction in wind directions, pest infestations, water cycles. Also, the question of what to plant next season can be resolved.
Data Science Salaries With Various Profiles
|Profile||Salary [1 to 4 years exp]||Salary [4+ yrs exp]|
|Data Scientist||₹610,811||₹1,004,082 & above|
|Data Warehouse Architect||₹884,372||₹1,495,713 & above|
|Data Analyst||₹407,100||₹636,949 & above|
|Machine Learning Engineer||₹505,561||₹693,249 & above|
|Business Intelligence Developer||₹445,919||₹873,510 & above|
|Statistician||₹405,880||₹1,000,000 & above|
To conclude, we say that if you choose a career in data science, then:
- You will find a boom in promotions.
- Great packages with handsome upgrades.
- If you are exceptionally talented, you will be a DATA SCIENTIST in 3-4 yrs easily.
- You can always upgrade and go towards ARTIFICIAL INTELLIGENCE.
So, choosing this career is the best decision you can take today. Think hard about it. Do some research. Get the knowledge on companies around you or in your city on what they are offering.
Ultimately, there is a lot to learn in Data Science, choose a profile and focus on that only. Don’t pull up too many things at a time. After all, you know, what profile you want.
That’s it. Get started and plan for a career in Data Science.