Data science can be a lucrative and satisfying career, with tremendous opportunities for growth. The jobs are among the highest paying and there are several perks. Covid-19 has accelerated the growth of data scientists in India, with massive chunks of data now being processed online. About 1,400 data scientists were working in India as of June 2021 and almost 2 in 5 of them were in Captive Centres established by MNCs in the country. The main benefits of considering a data science career path include the low entry barrier, opportunity to work in a new and upcoming field, good salary, and opportunities to learn and grow. Although this is a relatively new domain, data science is here to stay, as it enables businesses to gain key insights from unstructured data.
There are a few golden rules to follow if you dream of a thriving career in this field. Here’s a look at some of them.
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1. Pick a data science course
This is the first step if you are wondering how to pursue a career in data science. Knowledge of the theory and practical applications will help you understand the basic concepts. Check out the Data Science Course offered by NASSCOM-partner GeekLurn.
Features of the course
- 2-year program
- 6 months of live interactive sessions by industry experts
- 18 months of sponsored project work
- Get experience certificate of 1.5 years
- Get certified by top companies like Accenture, IBM, Microsoft, and Oracle
- 100% job guarantee
- Pay in EMIs
- 100% money back guarantee
- Enjoy scholarships from Day One
Actively attend the discussions, complete your assignments on time and do not hesitate to ask questions.
2. Practice maths
Maths helps develop skills of making connections, understanding patterns, quantifying relationships between data points, and employing these to draw conclusions or make predictions. All these abilities are critical for a data science career. In fact, maths forms the heart of statistics, machine learning (ML), and data analysis. Brushing up on arithmetic, linear algebra, calculus, geometry, probability, and Bayes theorem and how to apply these can help you start a career in data science. Practise solving equations with linear regression, beta and gamma functions and other theorems.
3. Polish your communication skills
Being technically sound is not enough for unlocking data science job opportunities. You will need good communication skills to succeed, since the work may involve attending meetings, sharing ideas and/or presenting your research paper. Your communication skills will also help you present your work to non-technical audiences, like C-Suite executives. Communication is also about listening, which helps you assimilate what another person is saying. Practising storytelling, data visualisation, and writing reports will help you kickstart your career in data science.
4. Improve your programming skills
In a survey on the preferred software development languages to learn among Indian IT professionals in 2020, around 35% chose Python. This is because Python is very simple to learn and straightforward to use. As a beginner, you can focus on SQL and Python, as both these technologies allow the storage of massive datasets and databases, which can help you get started with your data science career.
5. Read research papers
This is a great way to gain new knowledge. Data scientists come up with innovative concepts and publish their research papers. Since data science is a niche and fast-evolving domain, try to keep track of weekly papers being released to remain updated with the latest developments and hone your learning. By remaining abreast and adding to your knowledge, you can apply for different types of data science jobs.
6. Hone visualisation techniques
Visualisation in data science involves generating graphical and pictorial representations of data, which helps to understand the data better and draw insights from the dataset. You can practise seeing patterns in data and converting data into graphs and charts. The best way to practise this is by using trading charts.
Knowing a few common methods like circle view, bubble cloud, matrix, word cloud, heat map and histogram can also open more job opportunities for data science.
7. Showcase your work
For jobs after a data science course, you will need to build a portfolio. Consider creating a GitHub profile and sharing every project you have worked on, along with detailed descriptions and relevant links. You can also create a LinkedIn profile. These will lead potential recruiters to you. You can increase your online footprint by creating a personal blog, mentioning everything about you including your education and interests as well as uploading projects you have worked on. You can also try writing some short articles about the progress of data science or the latest developments in the field.
8. Be on the lookout for projects
To build a career in data science, begin with working on any project rather than waiting for your dream project. Even if the project is small, it will help you practise and add to your portfolio. Recruiters will be keen if you have at least a few data science projects in your portfolio, which increases the chances of you grabbing your dream project.
9. Build your resume
Choose a clean and professional-looking template and begin drafting your resume. Keep updating it as you hone your skills and work on more projects. It’s a good idea to create different versions of your resume, each customised for a different type of organisation or team. You can check job postings to know the specific skills that organisations are looking for and add the relevant ones to your CV. This increases the searchability of your resume.
10. Improve your focus
Data science requires patience and focus, as it involves seeking answers to complex questions. Cleaning, gathering and analysing data can become mentally exhausting. You need to identify ways of relaxing your mind and remaining focused. There are great data science job opportunities and polishing these non-technical skills can help you succeed in your career.
Data drives decision-making in businesses today. That’s the reason why data science as a career has gained immense popularity. Start adding to your skills today to improve your prospects ahead.
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.
