Data is the new oil – This saying holds in the current landscape, where companies globally are turning towards data science to solve some of the most eminent challenges.
With the demand for experienced data professionals increasing by the day, there’s a lot of interest in gathering information on how to become a data scientist.
If you are passionate about working alongside large volumes of data and solving complex problems, this career is for you.
This article gives you a quick and easy roadmap to pursue well-paid, high-growth careers in data science; while answering some common queries around the same.
So, what are you waiting for? Let’s dive deep right in.
What is a Data Scientist, and What Does it Do?
A data scientist is a trained professional responsible for collecting, analysing, and interpreting data to drive organisational decision-making and innovation. The role combines elements of mathematics, science, and computer programming.
In addition, it also involves the likes of advanced analytics and machine learning as some of the core skills to become a data scientist.
Data scientists often work with large amounts of data to:
- Develop hypotheses
- Make inferences, and
- Analyse market trends, stuck trades and cybersecurity threats, among others
Steps to Become a Data Scientist
Here’s a step-wise roadmap to start your career in data science:
Earn a Data Science Degree.
Although a degree in data science is not mandatory, employers always like to see some academic qualifications of the employee to ensure the person they’re hiring knows how to tackle specific tasks. A bachelor’s degree in data science, computer science, or statistics significantly helps one get employed sooner than others.
In addition, you can also pursue some online data science certifications offered by the likes of edX, Coursera, and Udemy.
Get Programming Skills
Getting proficient with programming is another crucial step. One must learn one or two programming languages to work around specific AI/ML models and to solve complex problems.
Here’s a quick overview of some popular Data Science-related program languages:
Python
You must learn Python and its libraries, such as NumPy and SciPy, to manipulate and analyse data.
You can also perform some AI and ML-related tasks with Python.
R
R is another programming language renowned for its statistical capabilities. It can be used for data visualisation and exploratory analysis.
SQL
SQL is used to search and analyse structured data sets stored in a database. It enables data scientists to extract relevant insights and perform data manipulations effectively.
SAS
SAS is used for mining and altering data from various sources. In addition, it can also manage and retrieve deleted data from a variety of sources.
Once the data is retrieved, you can process it using statistical analysis.
Learn Data Visualisation
As a data scientist, you should learn to create charts, histograms and graphs to represent the data visually. Doing this makes it easier for non-technical folks to understand the data and accelerate decision-making.
Here are a few tools you need to know for data visualisation:
- MS Excel
- Power BI
- Tableau
Machine Learning
As a data scientist, integrating machine learning into your work means continuous improvement in data quality. Knowledge of machine learning and incorporating it into your work also enables you to predict the desired outcome of this data.
Various Data Science certifications help you learn about Machine Learning and its applications in analysing and processing data.
Big Data
Learning big data helps you handle and analyse vast volumes of data to make data-driven decisions at scale.
Proficiency in technologies like Hadoop, Spark and distributed computing are important data-related skills you need to become a data scientist.
Develop Soft Skills for Higher Roles
Apart from technical proficiency, data scientists must also have in-depth business knowledge. They should be able to communicate while being flexible in their approach.
It also helps if you’re someone who believes in collaboration and teamwork.
Learn Tools
Learning different data science-related tools is another important skill to becoming a data scientist.
Here are a few of those that you need to master:
- Apache Spark
- Tableau
- SAS
- MATLAB
- Python
- R
- BigML
Get a Job as a Fresher
Getting a job as a fresher is the quickest way to become a data scientist. You need a good portfolio with industry-specific projects showcasing your skills.
You can start applying to some of these roles via FoundIt as well.
Prepare for Higher Roles
Once you’ve gained significant experience, it’s time to prepare yourself for better, high-paying roles.
To do this, stay updated with current industry trends and upskill yourself as much as possible.
Career Path for a Data Scientist in Malaysia
One can get started with a data analyst job as an entry-level professional.
Once you have worked for a while and acquired advanced skills and experience, you can expect to be promoted to Senior Data Scientist or the Director of Data Analytics in Malaysia.
Conclusion
Data science is taking over the world, and the demand for data scientists is skyrocketing. If you’re passionate about leveraging data for business and innovation, this is the field for you.
We hope the article was informative and helped you understand the various aspects of how to become a data scientist in Malaysia.
FAQs Related to Skills Required to Become A Data Scientist
Q1. What Skills Do Data Scientists Need?
Ans1. Data scientists should have the following skills:
· Critical thinking
· Problem-solving skills
· Programming and IT skills
· Understanding big data and related technologies
· Data analysis and manipulation
Q2. What are Some Common Tasks that Data Scientists Perform?
Ans2. Some of the everyday tasks performed by the data scientists include:
· Cleaning the data
· Organising the data into relevant data sets
· Preparing charts and graphs for data visualisation
· Statistical analysis and data research
Q3. What are Some Common Challenges that Data Scientists Face?
Ans3. Some common challenges faced by data scientists include the following:
· Understanding complex algorithms
· Dealing with handling massive data sets
· Creating unique data visualisations,
· Communicating these insights with non-technical stakeholders.
Q4. What is the Average Salary of a Data Scientist?
Ans4. The average data scientist’s salary in Malaysia is RM 6,883 per month.
Q5. What are the Educational Requirements to Become a Data Scientist?
Ans5. Most data scientist roles require a bachelor’s degree in technical fields like computer science or information science and statistics. Advanced degrees are not required mandatorily for having a career in Data Science, but an advanced degree always helps.
Employers are generally concerned with your skills rather than your educational qualifications.
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