Becoming a Data Scientist

The continuous change and innovation in digital technology has driven a massive shift in how businesses operate. Nowadays, data is seen as a critical asset, enabling companies to optimize their operations, gain deeper customer insights, and make data-based decisions. Because of this surge in demand for data analysis, learning how to get into the field of Data Science has become an increasingly popular study.

But, what is Data Science and why is it currently part of the noted top-paying tech jobs?

In this guide, we do a deep dive into Data Science and Scientists to understand exactly what they do and how to become one. We list down the steps to take to become a professional in this field and determine the essential skills you need to thrive.

So, What is Data Science?

Data Science is a multifaceted discipline that mainly focuses on extracting insights and information from vast amounts of raw data. Through the combination of techniques in mathematics, statistics, computer science, and domain knowledge, Data Scientists uncover patterns, trends, and relationships hidden within data.

Their findings are key to business success, driving innovative solutions to solving problems, predicting future outcomes, and making informed decisions.

What Do Data Scientists Do?

The daily routine of data scientists is a combination of their technical expertise and analytical thinking. Their responsibilities typically include:

Problem Framing: They collaborate with the organization’s stakeholders to understand business challenges and translate them into questions answerable by data.
Data Acquisition: Data can come from diverse sources like databases, sensors, social media platforms, and customer surveys. Data scientists gather and integrate this data for further analysis.
Data Wrangling: Raw data is rarely perfect. It’s a data scientist’s job to clean, organize, and format this information to ensure its accuracy and suitability for analysis.
Data Exploration: Data scientists generally use statistical methods, programming languages, and machine learning algorithms to identify the correlation between the collected data and its projections.
Modeling and Predictions: Data science experts can build models based on their analyses. These models can be used to predict customer turnovers, optimize marketing campaigns, or identify fraudulent activities.
Communication and Visualization: Aside from being number crunchers, data scientists are storytellers. Once they’ve translated complex data insights into clear and compelling presentations like charts and graphs, they can effectively communicate their findings to both technical and non-technical audiences.
Recommendations and Actionable Insights: Drawing on their analyses, data scientists suggest solutions and strategies to address business challenges.

According to Glassdoor, the estimated pay for data scientists in the Philippines is ₱66,708 per month with a potential to increase to ₱151,667 if you’re promoted to a managerial position. Generally, there are lots of varying reasons people choose to go into data science. However, the salary benefits are definitely one of the many motivations professionals think a Master’s in Computer Science is worth it .

How to Be a Data Scientist in the Philippines?

Becoming a data scientist in the Philippines requires a combination of education, skills development, and practical experience. Here’s a breakdown of what to do to guide you in becoming an industry expert:

1. Educational Foundation

A strong educational foundation is important to pursuing a career in data science. And while graduating from a data science program is ideal, it’s not mandatory. Relevant fields like attaining a bachelor or master’s degree in computer science, information technology, mathematics, statistics, and engineering can equip you with the essential analytical and problem-solving skills needed for the industry.

2. Bridge the Skills Gap

Taking online certifications, bootcamps, or short courses for IT in the Philippines can be excellent ways to fill the knowledge gaps and develop in-demand data science skills. These programs can provide intensive training for practical and theoretical knowledge, certifying your credibility as a data scientist.

3. Master the Core Skills

As mentioned earlier, data science is a blend of technical and analytical skills. The relevant skills needed to excel in data science are:

Math and Statistics: These topics are the bedrock of data science. A solid understanding of probability, hypothesis testing, correlation analysis, and regression analysis is invaluable to interpreting data.
Programming: Two of the most popular programming languages in data science are Python and R. Python is known for its versatility and readability, while R excels in statistical computing and data visualization. These tools will be your best friends as you become a data scientist.
Machine Learning: As data science evolves, machine learning becomes an important part of your progress. Grasping the core concepts and algorithms related to machine learning like supervised learning (classification and regression) and unsupervised learning (clustering and dimensionality reduction) enables you to build models that can learn more data and make predictions—much like using AI.

4. Build a Strong Portfolio

Your portfolio is a critical tool to showcase your skills and experience to potential employers. By participating in data science competitions and working on personal or freelance projects, you can demonstrate your capabilities and stand out in your profession.

5. Network and Build Connections

The data science community in the Philippines is growing fast. It’s important you actively connect with professionals on digital platforms like LinkedIn or online communities and forums.

Put yourself out there and attend industry meetups, conferences, and workshops to simultaneously build your network and learn the latest trends. Doing so can open doors to new opportunities and provide you with valuable mentorship.

Pursuing a career in data science in the Philippines offers exciting opportunities for growth and innovation, impacting various industries. With a strong educational foundation, continuous learning, and practicing the right skillset, you can pave the way for a rewarding career as a data scientist.