How To Become A Data Scientist: 7 Key Actions To Take

The rapid growth in data generation and the increasing complexity of data challenges have intensified the demand for skilled data scientists. These professionals are vital for analysing extensive data sets and transforming them into actionable insights that significantly impact business strategies. 

Forbes emphasises that despite the rapid advancements in AI technology, human expertise in interpreting and contextualising data remains crucial. Data scientists offer a unique blend of analytical skills and domain knowledge that machines cannot replicate, ensuring AI applications are practical and aligned with business objectives.

Understanding the path to becoming a data scientist is significant for those aspiring to enter this dynamic field. This journey involves technical skills, domain expertise, and practical experience. 

In the next sections, we’ll cover the qualifications and key steps to building a successful career in data science.  This guide will offer valuable insights and practical tips to help you make a meaningful impact in this exciting field.

What is a Data Scientist?

What makes someone a data scientist? A data scientist is a professional who deeply understands the mathematical and statistical methods used to analyse data and extract insights from it. They are also creative and can think outside the box.

Data science is a burgeoning field that involves analysing, modelling, and visualising data. With the exponential growth of data produced by digital activities, the demand for data scientists is at an all-time high, making it a field ripe with opportunities. 

7 Steps to Become A Data Scientist

Here are the steps you must take to become a data scientist in Singapore:

Develop Data Skills by Building a Broad Knowledge Base

Establish a firm grasp of the diverse aspects of data science before specialising in a particular area. A strong background in Mathematics, Engineering, Statistics, Programming, and IT will help you understand this field more efficiently. You also have to be proficient in Python, SQL, and Excel. These skills are important when you work with raw data and its management.

Build a Solid Foundation with Essential Data Science Tools

Enrol in an online course like Vertical Institute’s Data Science Bootcamp to gain essential skills. This course will teach you how to extract, organise, analyse, model, visualise, and present data using tools like Tableau. 

You’ll also gain proficiency in Python, a leading programming language that facilitates efficient data processing. In addition to Python, you’ll learn vital tools and techniques for data cleaning, analysis, and modelling. Focus on mastering these skills through practice to enhance your employability and increase your chances of securing a data scientist role.

Work On Projects To Build A Portfolio

Build a polished portfolio to showcase your skills and impress prospective employers. More than a certification in data science, employers want to see that you can do the job. Being involved in various projects also allows you to practise your new skills while challenging yourself.

With Vertical Institute’s Data Science Bootcamp, you can participate in a capstone project that you can proudly include in your portfolio. This real-world project experience concludes students’ learning by using new tools and concepts they have learned throughout the course.

Stay Updated with Industry Trends

The data science domain is constantly progressing, introducing new tools, methods, and standards. Staying updated through industry publications, attending online seminars, and interacting with professional groups will help you stay ahead and adaptable.

Gain Practical Experience through Internships or Part-time Roles

Hands-on experience is highly valuable. Internships or part-time positions allow you to apply your knowledge in a real-world setting and learn from the insights of experienced mentors. For instance, an internship at a leading tech company will involve working on real data projects, which will help you refine your analytical skills and see how theoretical concepts apply in practice. This exposure provides both practical experience and valuable mentorship from industry professionals.

Apply To Relevant Data Science Jobs

Data scientists may have different titles depending on their industry. Hence, you must identify your strengths, goals, and relevant specialities to determine which career path you would like as a data scientist. Here are some examples of in-demand data science roles across industries:

• Data Scientist – utilises statistical methods, machine learning, and analytical approaches to uncover insights from complex data.
  
  
• Data Analyst – gathers, processes and analyses data statistically to reveal trends and support organisations in making data-driven decisions.
  
  
• Data Architect – responsible for designing, creating, and managing data systems and structures, ensuring data flows efficiently and securely within an organisation.
  
  
• Data Engineer – develops and manages the systems and tools required for data collection, storage, and processing, ensuring efficient and effective data operations.
  
  
• Quantitative Analyst – applies mathematical models and statistical techniques to analyse financial data, assess risks, and support investment decisions.
  
  
• Database Administrator – responsible for the upkeep and management of databases, focusing on performance, security, and data integrity, as well as handling tasks related to data backup and restoration.
  
  
• Analytics Manager – leads the analytics team, coordinates data projects, and creates strategies to leverage data insights for fostering business growth and informed decision-making.
  
  
• AI Research Scientist – explores and develops new artificial intelligence algorithms and technologies to advance the field and create innovative AI solutions.
  
  
• Business Intelligence (BI) Developer – designs and implements BI solutions to analyse and visualise data, creating dashboards and reports that help organisations make informed business decisions.
  
  
• Machine Learning Engineer – designs, creates and deploys machine learning models and algorithms to develop systems that analyse data and make predictive insight.

Network with Professionals

A well-developed professional network can open doors to new job prospects, collaborative opportunities, and expert career advice. For instance, attending the Singapore FinTech Festival can connect you with influential figures and potential mentors in the data science and AI sectors. Additionally, engaging with Singapore-based tech communities and LinkedIn networks can provide career benefits and professional growth.

Take the First Step Now and Embark on Your Data Scientist Journey

Technological advancements and Singapore’s role as a tech hub are driving a significant increase in the demand for data scientists in the coming years, attracting both startups and major tech companies. You’ll be well-prepared to pursue your dream job with the right skills, training, and a great portfolio.

About Vertical Institute

Vertical Institute prepares individuals for the jobs of tomorrow. We specialise in teaching in-demand skills, building the next generation of changemakers and inventors through our world-class tech courses and certifications. 

Singaporeans and PRs can receive up to 70% IBF Funding off their course fees with Vertical Institute. The remaining fees can be claimable with NTUC UTAP Funding or SkillsFuture Credits.