Data Scientist

Introduction

Kickstart your career with NTTS’s G.L.O.W Graduate Program, the ultimate launchpad for your tech career!

G – Grow in accelerated development path

L – Lead yourself with purpose & commitment

O – Own your career journey

W – Way Forward

Our comprehensive one-year program is tailored to empower talented and driven graduates like you with valuable hands-on experience, exposure to industry experts, and a diverse range of projects that will sharpen your skills and broaden your understanding to the ICT industry.

We are seeking a highly motivated and curious Junior Data Scientist to join our data team. This role is ideal for fresh graduates who are passionate about data, analytics, and solving real-world problems using machine learning and statistical techniques. You will work closely with experienced data scientists and engineers to build data-driven solutions that drive business value.

Responsibilities

• Assist in collecting, processing, and analyzing large datasets from various sources.

• Build and evaluate predictive models using machine learning algorithms.

• Support the development of data pipelines and automation workflows.

• Create visualizations and dashboards to communicate insights to stakeholders.

• Collaborate with cross-functional teams to understand business needs and translate them into data science solutions.

• Stay updated with the latest trends and tools in data science and AI.

Requirements

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.

• Strong foundation in statistics, data analysis, and machine learning concepts.

• Proficiency in Python or Ruby, and familiarity with libraries such as pandas, scikit-learn, NumPy, or TensorFlow.

• Experience with SQL and data querying.

• Good communication and problem-solving skills.

• Eagerness to learn and grow in a collaborative environment.

Preferred / Added Advantages

• Participation in data science internships, innovation programs, or competitions (e.g., Kaggle, hackathons, university challenges).
• Experience with real-world datasets or academic projects involving predictive modeling or data storytelling.
• Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and tools like Jupyter Notebooks or Git.