What is Data Science? Scope and Career Opportunities

Being a Data Scientist is one of the hottest and trending career option of the decade. The demand for data scientists is huge, the number is said to be much higher than the available candidates. So, choosing data science as a career option has a lot of scope and will remain so in the near future.

For some interesting information about data science, read this story.

What is Data Science?

Data Science basically is an amalgamation of mathematics, programming, statistics and design which are applied in order to successfully manage digital data collection.

The main 3 components involved in data science are organising, packaging and delivering data. Overall, it is a multidisciplinary blend of data inference, algorithm development and technology in order to solve analytically complex problems.

So what does a Data Scientist do? or Who is a Data Scientist?

Data Scientists are those who perform data science. A Data scientist performs research and analyses data and help companies flourish by predicting growth, trends and business insights based on a large amount of data.

Basically, data scientists are big data wranglers. They take this huge data and use their skills in mathematics, statistics and programming to clean and organise the data. All their analysis combined with industrial knowledge helps to uncover hidden solutions to business challenges.

A day in life of a Data Scientist

On a given day, a data scientist will have to do the following tasks:

Generally, a data scientist needs to know what could be the output of the big data he/she is analysing. He/she also needs to have a clearly defined plan on how the output can be achieved with the available resources and time. Most of all the data scientists must know the reason behind his attempt to analyse the big data.

To achieve all of the above, a data scientist may be required to:

• perform research on the messy data available and frame questions that needs to be answered by his analysis on the data collected
• collect huge data from multiple sources.
• make use of high-end analytics programmes, machine learning and statistical methods to organise data into a predictive model
• clean the huge volume of data to discard irrelevant information
• explore and analyse the data to determine the trends, opportunities and also weaknesses
• produce data-driven solutions to conquer the most pressing challenges
• invent new algorithms to solve problems
• Build new tools to speed work
• communicate the predictions from the data analysed through data visualizations and reports
• recommend effective changes for the existing strategies to companies

Who is a good data-scientist?

Data analysis sometimes results in counter-intuitive insights.

A good data scientist is one who has a business context in his data analysis solutions. He/she should be able to convert the stories numbers tell into actionable form. A data scientist needs to have an eye to details as well as the big picture.

Who can be a data scientist?

A Data scientist is sort of 'jack-of-all-trades' for data crunching. Basically, 3 main skills a data scientist needs to possess are mathematics/statistics, computer programming literacy and knowledge of particular business.

What are requisite skill set to be a data scientist?

As discussed above, data science is a beautiful blend of 3 major domains. Expertise in mathematics, technical and programming skills, business and strategy awareness combine to form Data Science.

Mathematics and Data Science - The core of building data product is the ability to view the huge volumes of data quantitatively. Building analytic models to solve business problems is usually hard math.

Though statistics is an important part of data science, it is not the only type of math utilised. Many inferential techniques and machine learning and linear algebra are used by data scientists. It is necessary for a data scientist to have an overall depth of knowledge in mathematics.

Technical and programming skills - Using technical skills to wrangle enormous data to create genuine solutions require complex programming skills. Data scientists need to be able to code - prototype quick solutions, as well as integrate with complex data systems. Core languages associated with data science include SQL, Python, R, and SAS. On the periphery are Java, Scala, Julia, and others.

Strong Business strategies - A data scientist must be able to view data through business lens. This helps translate the data observations made to solve business problems. Data scientists use the data insights as support to build better business strategies.

What is the payscale of a data scientist?

• A data scientist earn an average salary of Rs 6,00,00 per year. Experience influences the income of this job.
• The salary for a data scientist abroad can range anywhere from $100,000 to $120,000.