How to Become a Data Scientist (Skills and Qualifications)
Updated 26 January 2023
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Data scientists are part of the information technology or data science team who help in analysing data to provide information that helps the organisation make data-driven decisions and create strategic plans. With the development of the internet economy, the pace of data generation has increased, leading to a steep increase in demand for data scientists. If you love complex problem solving with the help of technology, a data scientist can be a very good career option for you. In this article, we discuss how to become a data scientist, their roles and responsibilities and the skills required to succeed.
Related: What Does a Data Scientist Do? And How To Become One
How to become a data scientist
You can consider taking the following steps to become a data scientist:
1. Earn a bachelor's degree
Most data scientists earn a bachelor's degree, preferably in science streams like engineering, maths, IT or any other related field. Having a bachelor's degree in a quantitative field can help you in enhancing your problem-solving abilities through analytical and critical thinking, which are some of the most important skills to possess as a data scientist. You may also consider doing an internship during your bachelor's degree, which might help you in getting an entry-level role in this field. This can also help in getting first-hand knowledge of a corporate setup and day-to-day responsibilities of a data scientist.
2. Get certifications
Getting certifications can help you in enhancing your skill set and showcasing your interest and seriousness in becoming a data scientist to potential recruiters. There are a number of courses on data science and data analytics available online on various websites. You can consider joining any of these courses to improve your skills and chances of securing a job as a data scientist. You may also consider getting certified by various educational institutes in India that provide courses in data science. Some of these institutes may also help you in getting a placement as a data scientist in various companies as part of their programme.
3. Gain work experience
Data scientists continue to be in high demand across industries. You may consider getting the relevant experience as a data scientist by doing internships or entry-level jobs as a junior data scientist or junior data analyst. Gaining relevant work experience can help you in enhancing your skills and getting first-hand knowledge of a corporate setup. Getting work experience can help in making your resume more attractive to employers and increase your chances of getting shortlisted for the position of a data scientist. Also, working in an entry-level position, companies may provide on-the-job training and certifications that can lead to promotions.
4. Build your portfolio
You may want to build a portfolio of some of the major projects that you have worked on in the past to showcase your abilities to recruiters and gain an advantage over other candidates. You can include examples of projects that you have managed in your previous organisations in a visual format to provide evidence of your capabilities and skills and showcase the impact you have created in the past. You can take help from various online resources on things like templates to use while building your portfolio to make it exciting and appealing to potential recruiters.
Related: How To Make a Portfolio: A Step-by-Step Guide
5. Pursue a master's degree
Pursuing a master's degree in data engineering, computer science, business administration or a related field can help you to obtain a leadership position in the data science field. Having a master's degree might also give you an advantage over other data scientist candidates when applying for higher-paying jobs. You can check the details and requirements of various programs offered by a variety of institutions to see if they align with your desired career path and if they can provide you with the necessary skills and exposure to excel in this field.
6. Pursue a doctorate
Some data scientists also pursue a doctorate in computer science, data science or any other related field to achieve leadership positions in their organisations and get high-paying jobs. Having a doctorate might position you to earn a teaching position or a higher-paying role as an executive within an organisation with industry expertise. Doctorates are highly skilled and knowledgable in their respective domains and are often in high demand across industries to bring innovation and excellence.
What does a data scientist do?
Data scientists deal with huge amounts of data to analyse and predict future business scenarios. They manage structured and unstructured data, analyse it and build mathematical models to provide recommendations to business leaders and help them in making key decisions for the company. Data scientists use a variety of software and tools. They work with large computer databases to extract data, manipulate codes to make sense of data and use statistics to prove and disprove the various hypotheses. Data scientists are skilled in mathematics and analytical abilities and provide recommendations to people at the leadership level.
Some specific roles and responsibilities of a data scientist include:
extracting and collecting data from various resources
cleaning the data to increase its accuracy and reliability
analysing data to find any patterns or trends
processing, managing and storing data
using various statistical algorithms to predict or forecast future trends and scenarios
showing data in a visual format that is easy to understand and comprehend
preparing reports and presentations for leadership of the organisation
Skills required to become a data scientist
Some of the skills you may need to become a successful data scientist include:
Technical skills
Data scientists work on computers to analyse data and make predictions for which excellent technical skills are required. They often have exceptional maths and computer skills which help them to thrive in this role. Data scientists are very good in programming languages, statistics and probability, which helps them to interpret data and make calculated decisions on the organisation's behalf.
Related: Technical Skills: Definitions and Examples
Communication skills
Data scientists are often required to communicate their analysis and findings to their managers and company leadership, which requires superior communication skills. Written communication skills are essential to build reports and presentations that communicate the ideas in a crisp and clear manner. Oral communication is essential to articulate your thoughts and put forward suggestions to the relevant audience. Being clear and concise, practising empathy, asserting yourself while being calm and using your body language to put forward your point are all essential components of good communication skills.
Related: Communication Skills: Definitions and Examples
Analytical skills
Data scientists have superior analytical skills which help them to visualise a problem from all possible angles and provide solutions after considering and evaluating all the possible solutions. They review and check the accuracy of data and information and analytical skills help them do this seamlessly. Your ability to visualise numbers, analysing them and converting them to mathematical relations to provide solutions can help you become a good data scientist. Data scientists are able to visualise how different factors interact with each other, which helps them solve business problems efficiently.
Related: Analytical Skills: Definition, Tips and Examples
Time management skills
Data scientists may have to work on multiple projects with strict deadlines and time management skills are essential to make sure that they are able to deliver on time. Time management skills help data scientists use their time in an efficient manner and achieve the desired objectives and results. Preparing schedules and following them strictly, fixing deadlines, setting long- and short-term goals, managing your time effectively and prioritising your assignments are all key constituents of time management skills.
Related: Time Management Skills: Definition and Examples
Salary of a data scientist
Data scientists are some of the highest-paid professionals in the tech industry. The average salary of a data scientist is ₹8,50,429 per year. This figure can vary depending on the location. For example, the average salary of a data scientist in Chennai, Tamil Nadu, is ₹10,90,791 per year. In Mumbai, Maharashtra, a data scientist earns ₹9,75,898 on average.
Data scientist work environment
The exact work environment and responsibilities of a data scientist may vary depending on the organisation and industry. However, some aspects of their routine remain almost the same:
work on desks for most part of the day
coordinate with other stakeholders to understand business requirements
extract data and set data processing processes
clean data to make sure the analysis is not skewed
test and learn various statistical algorithms
write reports, build a proof of concepts and build dashboards for reporting purpose
Working in the data science field requires discipline, focus and patience. As this is a relatively new field, new inventions and tools are being launched in the market every single day. A data scientist needs to upskill regularly and learn new technologies now and then to stay relevant in this industry.
Salary figures show data listed on Indeed Salaries at the time of writing the article. Salaries may vary depending on the hiring organisation and a candidate's experience, academic background and location.
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