Everything You Need to Know Before Choosing a Career in Data Science

Data Science as we know it has existed for much longer than imagined. Its current iteration is the most evolved and advanced, with innovation leading it still further. If you are new and looking to take advantage of the opportunities opening within the field, continue to read as we explore the intricacies of the data scientist career. 

Who are Data Scientists and what do they do?

A data scientist is a professional who extracts and analyses many structured and unstructured data using mathematics and statistics to solve problems by predicting or analysing what comes next and providing informed recommendations for strategy. Every data scientist must be skilled in ensuring that extensive unruly data can be made accessible, clear, and actionable. They are usually highly educated, technically trained individuals possessing either a master’s degree or a PhD. 

Data scientists are tasked with asking and answering important and relevant questions to understand the issue at hand. They work alongside professionals, executives, and other business stakeholders to understand the objectives and goals and provide them with the information required to achieve these goals. Generally, data science follows a life cycle – Capture, Maintain, Process, Analyse and Communicate utilising tools like data visualisation, statistical modelling, machine learning, deep learning, pattern recognition, and text analytics. The infographic below details the different tasks involved in each stage of the data science life cycle.

Important skills for a data scientist job include analytical skills, good communication ability, critical and logical thinking, statistics and math knowledge, and teamwork. Glassdoor examined the 10 most common skills in job postings. Python, SQL, R, JAVA, Hadoop, and Tableau are a few of the hard skills mentioned that are important for all data scientists to learn. 

What are the possible Career Paths in Data Science? 

Data science is a large multidisciplinary field with a variety of options for pursuing a career. Data science careers can fall into four categories – Data related, Product related, Engineering, and Business. Here are a few of the most common and widely known career paths that are currently shaping the future of data science. 

Data Scientist – The primary role of a data scientist is to clean and analyse massive amounts of raw data, create reports, and provide valuable insights that should affect a business’s decision-making capabilities. Not to be confused with data analysts, data scientists require more technical knowledge. 

Data Analyst – While data scientists answer questions about the future, data analysts usually try to understand trends and patterns that have happened in the past to aid in decision making. They handle large datasets and analyse data to communicate effectively to organisational leaders about trends and insights.

Machine Learning Scientist – The role of a machine learning scientist combines the coding, analytical, statistical and mathematical expertise of a data scientist with the capabilities of a software engineer to design software for predictive modelling automation using deep learning techniques.

Application Architect – Application architects design and develop software applications, tracking their usage within businesses to understand interactions between each component and users. 

Enterprise Architect – They are responsible for ensuring that an organisation’s strategy aligns with the technology required to execute functions. 

Data Architect – Data architects take care of all things related to an organisation’s data. Not only do they create new data systems, but they also maintain and improve existing systems.

Data engineer – Their primary role is to focus the building, managing, and optimising data pipelines that create an interconnected data ecosystem that makes information readily available for data scientists. 

Statistician – Statisticians collect, analyse and interpret data. They are involved in design and process and communicate their findings to inform stakeholders and aid decision making. 

It is crucial to understand which path within data science best suits you as each requires a unique set of skills. Head on over to our blog to learn the Top 10 skills required for a Data Scientist. 

What is the Data Science Job Market like?

We are observing a boom in the interest in data science as a career. A quick peruse through job search websites like LinkedIn, DevNetJobs, Indeed, or Monster will reveal several Data Scientist jobs available. 

According to the U.S. Bureau of Labor Statistics – Beyond Numbers, data science and mathematical science occupations are projected to grow by 28% from 2016 to 2026, resulting in about 50,500 new jobs due to the increased use of big data by businesses and governments. 

In India, according to the report on Analytics and Data Science jobs in India for the year 2020, approximately 93,500  data science jobs were vacant as of August 2020, contributing to 9.8% of the total global analytics job openings. Despite the recessionary effects of the pandemic on the job market, the report stated a significant jump in the total global job openings in data science at 7.2% in January 2020. The interest in the field of data science has never been higher. Professionals and companies alike are recognising the value of data and its impact on every aspect of decision-making. 

Why is there a demand in the field of Data Science?

Data science has become such an essential field of study as more businesses want to capitalise on its numerous benefits. These days companies deal with large mines of unstructured data. Data science provides the advanced tools required to make sense of this data for practical use in any enterprise. Almost every industry uses data scientists to their advantage, be it retail, financing, banking, or healthcare. Hence, the demand for qualified and skilled data scientists remains high. 

How is Data Science applied across industries?

Healthcare – Data science can be applied in so many fields of study. In the healthcare industry, it is used to identify and predict diseases like a flu outbreak, personalised recommendations for current cancer patients based on past experiences using machine learning, and even in period trackers where data is mined to remind women of the stages of ovulation cycles.

Urban Planning – It is also used in road travel by optimising travel routes in real-time like in Google Maps, learning traffic patterns, and even identifying commuters using multiple transit modes. All of this is used to inform city planning and commuter transit design. 

Sports – In sports science, data science plays a huge role in recruitment, using in-game statistics to predict player potential. 

Public Affairs – Government authorities use data science in the form of facial recognition and fraud detection. 

Marketing – It provides insights for intelligent advertising technology, personalised ads, social media marketing. This is just a tiny peek into the number of different ways data science plays a vital role in all aspects of life.   

What is the salary structure in Data Science?

Data science is a fast-growing field and is one of the highest-paid fields. According to the U.S. Bureau of Labor Statistics, as of May 2020, the median annual wage is $103,930. The industries with the highest published employment and wages for data scientists and mathematical science are Computer Systems Design and Related Services ($111,490), Management of Companies and Enterprises ($107,980), Management, Scientific, and Technical Consulting Services ($100,800), Scientific Research and Development Services ($109,601) and Insurance Carriers ($104,670). 

With more experience, data scientist salaries also increase. Research by PayScale found that a data scientist at an entry-level position with 1-year experience can earn an average wage of about $85,304 based on 1,337 salaries. Those with more than 20 years of experience earn an average salary of $135,836. 

It is the perfect time to pursue a career in data science as the demand for data scientists is currently high while supply is low. If you are looking to get started, consider checking out the Certificate Program in Business Analytics & Artificial Intelligence from Virginia Tech India. For more information on Data Science and to gain further insight into the industry, check out Top 10 Career Paths of the Future – Artificial Intelligence.