Vast amounts of data are generated from people searching for information on the net, browsing through sites, online shopping and social media. Data is also retrieved from machine-to-machine communication. Data science involves the study of such massive volumes of data. It uses advanced tools and techniques to identify patterns and derive meaningful information that drive business decisions.
With rapid internet penetration, smartphone adoption and digitalisation, the data generated has surged exponentially over the past few years. With this, data science has also prospered, and the trend is expected to continue. The global data science platform market, which was valued at $31.05 billion in 2020, is predicted to reach $230.80 billion by 2026. That represents a growth rate (CAGR) of almost 40%.
All roles in this domain, from data analysts to research scientists, come together to derive strategic insights from data. But sourcing, processing, gathering and analysing massive volumes of data requires some specialised skillsets. An aspiring data scientist must have a solid foundation in maths and statistics. Some knowledge of the relevant programming languages is essential too. One also needs a plethora of other technical and non-technical data scientist skills as well as some important soft skills to get noticed by prospective employers. So, here’s a look at some of the skills you will need to have a successful career in this domain.
Table of Contents
Technical Skills
You would need some special knowledge and expertise to perform specific tasks in data science. Apart from an understanding of concepts, you will need to be familiar with some tools to operate in real-world scenarios. Explore GeekLurn’s Data Science Architect Program to position yourself for interesting, fruitful and lucrative jobs in this segment. Being a partner of NASSCOM and IBM, GeekLurn offers a course that makes you industry ready and boosts your earnings potential. It spans 24 months, with live interactive classes and sponsored project work. You get a project experience certificate and a 100% job guarantee. You can seek guidance from eminent industry experts and mentors, participate in workshops and have a deeper understanding of technical terms and trends. Here are the top skills required to master data science.
1. Machine Learning
ML is a branch of Artificial Intelligence. The Indian AI market was valued at ₹472.73 billion in 2020 and is predicted to grow to more than ₹2 trillion by the end of 2027. Machine learning is a rapidly emerging technology that is at the core of data science. It helps analyse and examine chunks of data automatically and in real-time. ML is one of the top skills required for data scientists since they can use it for descriptive analysis, predictive analysis, diagnostic analysis and prescriptive analysis.
2. Statistics
Statistical computing and different approaches to statistics, like maximum likelihood estimators and distributors, are a few skills needed for data scientist-related job profiles. Statistical concepts and formulas can be used to review, analyse and interpret data, which play a key role in offering actionable inputs to businesses. You need to ensure you can communicate complex insights in an easy way to non-technical decision makers.
3. Programming
This is one of the top things a data scientist should know to flourish in their field. The most common languages to learn are Python and R. Others are Perl, SQL, C/C++, Hive, Pig, SAS and Hadoop. They help in exploring, cleaning and presenting data. Knowledge of programming also helps data scientists to send large volumes of instructions to computers and interact with them.
4. Data Visualisation
It is one of the important data scientist qualifications that help turn dull and boring numbers into easy-to-digest content. The process includes translating overwhelming amounts of business data into pie charts and graphs.
Studies show that managers with visual data recovery tools are 28% more likely to find information on time than those who rely on managed dashboards and reporting. Data scientists need accuracy and precision to create an interactive visual model with all the features, cutting down the need for too many words. It saves time and boosts efficiency in decision making.
5. Deep Learning
This is a neural network with three or more layers, including predictive modelling and statistics. The structure is based on the human brain to identify patterns and information and finally perform tasks. With deep learning, machines can make decisions almost like humans would. It can make collecting, analysing and interpreting large amounts of data faster and easier for data scientists.
Non-Technical Skills
Outside the technical realm, it is necessary to build and polish a few soft skills too. A mix of technical and non-technical skills can help to advance your career. The soft skills required to master data science are critical thinking, effective communication, proactive problem solving and a sense of the business you are working with. These would be necessary whether you are in an entry-level role or a managerial position. Being able to add these to your resume can help create an impact on potential employers.
The bottom line
A detailed understanding of what skills are required for a data scientist will help you pick the right certification course. Further, you will also be able to identify job opportunities that require skillsets that match yours. Even if you are unable to gain expert-level knowledge, familiarity with basic concepts can help your career prospects.
Neel Neeraj
Neel is a Product Manager with an interest in Data Science, Machine Learning, Cloud Computing, DevOps, and Blockchain with expertise in Python, R, Java, Power BI and Data analytics.
