Your Guide to Rewarding Data Science Careers and How to Get Started in Singapore

September 10, 2022

Your Guide to Rewarding Data Science Careers and How to Get Started in Singapore

Be Equipped With The Skills You Need To Be A Data Scientist  

As the demand for data scientists increase, it presents an enticing career path for students and existing professionals. This includes those who are not data scientists but are obsessed with data and data science, which has left them asking about what data science skills and big data skills are needed to pursue careers in data science.  

Data science continues to rise as one of the most in-demand career paths in technology today. Beyond data analysis, mining, and programming, data scientists program codes and combine it with statistics to transform data. These insights can help businesses derive return on investment (ROI) or help organizations measure their social impact.

The data science field is interdisciplinary and integral to society’s basic functions, such as restocking grocery stores, tracking political campaigns, and keeping medical records. It can be a fascinating and fulfilling career.

There are many career opportunities within data science. Here’s a guide to what data science is, the skills required, job types, and how to get there.

What Is Data Science? Definition, Skills, And Job Outlook:

Data science grew out of statistics and data mining. This is a new specialty, with the Data Science Journal making its debut only in 2002. It sits at the intersection of software development, machine learning, research, and data science while falling under the categories of computer science, business, and statistics combined.

Data professionals create algorithms to translate data patterns into research that informs government agencies, companies, and other organizations. Data science exists because information technology is evolving at a rapid pace, and there is a need to have for professionals to work in this field.

Skills Required In Data Science

In a field like data science, there are a number of technical skills that are helpful to have before diving in, such as:

  • Machine learning
  • Data visualization
  • Python Programming
  • Ability to manage unstructured data
  • Big data processes,
  • Communication skills
  • Storytelling
  • Critical thinking and logic
  • Business acumen

Leveraging the use of Big Data as an insight-generating engine has driven the demand for data scientists at the enterprise-level across all industry verticals. Whether it is to refine the process of product development, improve customer retention, or mine through data to find new business opportunities, organizations are increasingly relying on data scientist skills to sustain, grow, and stay one step ahead of the competition. Also, in this article, we will dive into technical and non-technical data scientist skills.

Types Of Jobs You Can Do With Data Science

Data science job roles:

There are plenty of data science jobs to choose from. All of them are integral to making key business decisions. Often, several of the job types below will work together on the same team.

Data scientist

Data scientists build models using programming languages such as Python. They then transform these models into applications. Often working as part of a team, for example, with a business analyst, a data engineer, and a data (or IT) architect, they help solve complex problems by analyzing data and making predictions about the future. This role is typically considered an advanced version of a data analyst.

Data analyst

Data analysts, unlike data scientists, use structured data to solve business problems. Using tools such as SQL, Python, and R, statistical analysis, and data visualization, data analysts acquire, clean, and reorganize data for analysis to spot trends that can be turned into business insights. They tend to bridge the gap between data scientists and business analysts.

Data architect

Data architects create the blueprints for data management systems, designing plans to integrate and maintain all types of data sources. They oversee the underlying processes and infrastructure. Their main goal is to enable employees to gain access to information when they need it. 

Data engineer

Data engineers prepare and manage large amounts of data. They also develop and optimize data pipelines and infrastructure, getting the data ready for data scientists and business analysts to work with. Data Engineers make the data accessible so businesses can optimize their performance.

Machine learning engineer

This role is not an entry-level position, but one you can build toward as a data scientist or engineer. Machine learning uses algorithms that replicate how humans learn and act, to interpret data and build accuracy over time. As part of a data science team, machine learning engineers research, build, and design artificial intelligence that facilitates machine learning. They also serve as a liaison between data scientists, data architects, and more. 

Business analyst

As a business analyst, you’ll use data to form business insights and make recommendations for companies and organizations to improve their systems and processes. Business analysts identify issues in any part of the organization, including staff development and organizational structures, so that businesses can increase efficiency and cut costs.

The Path To A Data Science Career

With so many exciting options in data science, you may be wondering where to begin. Whether you are just starting your career or switching from another one, here are the steps you can take to build toward your future in big data or machine learning. Join our Graduate Diploma in Data Science and Artificial Intelligence, a 6 months Part-time Programme where you will learn all the skills you need to advance your career in Data Science and Artificial Intelligence.

Recommended Programs

Gain Practical Decision Making Using Data Science.  The Graduate Diploma in Data Science & Artificial Intelligence course, helmed by Aventis Graduate School Singapore, focuses on equipping you with various aspects of data science—from the solid foundations of probability and statistics to on-the-job usage of machine learning models.

Leverage the power of Data Science to make decisions. Masterclasses from Industry Experts | No Programming Experience Required

After completing this program you should be able to:

  • Understand how to use data to derive meaningful results for your business.
  • Identify opportunities at your workplace where data science capability can be leveraged.
  • Understand different data science algorithms which are used to generate results.
  • Build and spearhead data science teams in the right direction.

Join over 3,000 Successful graduates. 

Embark on your learning journey with us today, find out more at Save on Programme fees with referral and enjoy up to $1,000* savings when you invite your colleagues to join you!

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