Data Scientist

Q1: What industry are you in?
A1: Data Scientist

Q2: Can you tell us about your personal work background and career path?
A2: As a graduate with a Bachelor of Science degree in Risk Management and Business Intelligence, I've always been interested in deriving insights from data and leveraging different tools. This natural inclination made joining the data industry a natural fit for me.

I started off my career in the Data Analytics and Research space, where I focused on deriving actionable insights from data, typically by analyzing data distributions and trends using simple analytics tools like Excel.

I then gradually moved into data reporting with Business Intelligence (“BI”) tools. This involved creating dashboards and regular reports about business historical performance, helping business users better understand the actual business scenarios and act on them accordingly. This required knowledge of BI tools, such as PowerBI and Tableau.

I subsequently made a move and am currently in the area of Machine Learning & Artificial Intelligence, which is the data science field.

My current role is at the #1 insurance company in the APAC region.

Overall, I've worked across more than 5 different industries, all related to data analytical work.

Q3: What are the responsibilities of your current role, and what do you enjoy about it?

A3: Daily responsibilities could vary by seniority.

For Junior to Mid-Level colleagues, it would involve hands-on programming for various tasks with examples below:

• Building predictive models to improve financial outcomes (e.g. Targeted communication to selected customers with the highest potential to purchase certain products, identifying the best potential hires, fraud detection, etc)

• Automating operations with AI models (e.g. language translation, image detection)

For Senior-Level colleagues, it would involve more managerial tasks with examples below:

• Engaging with business stakeholders

• Delivering presentations

• Designing analytics roadmaps and strategies

• Managing a team of junior data scientists

• Delivering high-impact projects

 Key Reasons I Enjoy this Role:

• Working with different departments on a variety of projects

• Rapid learning of business knowledge within the industry

Q4: Could you share a memorable professional experience?
A4: The technology in this field is cutting-edge and evolving rapidly, allowing me to engage with talents from tech giants like Microsoft, Google, Amazon, etc.

Attending industry conferences also exposes me to the latest AI advancements and enables networking with diverse professionals.

Q5: What personality traits are well-suited for this profession?
A5: Individuals who possess a strong growth mindset and self-learning capability. They should also enjoy computer programming and mathematics. 

Q6: Are there any considerations or limitations in this profession?
A6: Due to the rapidly changing technology in this field, the need to constantly learn is crucial to staying competitive. In addition to strong technical skills, a successful career in this field also requires good communication abilities to effectively pitch ideas to the business. 

Q7: How can someone enter this profession, and what are the promotion opportunities?
A7: One can enter this profession by demonstrating strong technical skills, such as knowledge of statistical models, BI tools, and programming languages like Python. A proven ability to learn is also crucial, which can be showcased through school projects, side projects, online course certificates, or bootcamp experiences.

 It is not mandatory to have an IT or statistics degree to join this industry (this will be a bonus), as much of the knowledge can be self-taught. What's more important is for individuals to demonstrate what they have learned and achieved through their side projects.

For individuals considering to be involved in side projects, I would recommend checking out the Kaggle platform (https://www.kaggle.com). It is owned by Google and offers unique opportunities to learn from expert communities and work on hands-on projects through public competitions (e.g. such as image recognition, housing price forecasts, and movie recommendations). One project I had the opportunity to work on was Netflix's movie recommendations. The goal was to recommend movies to users based on their past viewing behavior.

 Promotion opportunities are substantial for the right individual - someone who not only possesses the technical expertise, but also demonstrates a business-oriented mindset and the ability to effectively execute ideas using the available technical tools.

Some work-related photos below

My Office Building

By David, a data scientist in the #1 insurance company in APAC

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