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Data Scientist Intern

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This job is a Data Scientist Intern at Razer, where you'll help improve AI-based game recommendations. You might like this job because you'll work on global projects, get hands-on experience, and be part of a vibrant, gamer-centric culture!

Undisclosed

Singapore, Central

Job Description

Joining Razer will place you on a global mission to revolutionize the way the world games. Razer is a place to do great work, offering you the opportunity to make an impact globally while working across a global team located across 5 continents. Razer is also a great place to work, providing you the unique, gamer-centric #LifeAtRazer experience that will put you in an accelerated growth, both personally and professionally.

Job Responsibilities :

By the end of the internship, you will gain practical experience in the application of data science techniques in recommendation using industry’s best practices and modern data technologies.

Main Tasks & Responsibilities:

Join our Big Data team as a Data Scientist Intern (Personalisation) and work on large-scale AI systems that power personalised product recommendations across Razer.com, Cortex, Synapse, and other platforms. This role sits at the intersection of data engineering, cloud infrastructure, and artificial intelligence.

You will collaborate with data scientist and engineers to:

  • Develop and enhance AI-driven personalised recommendation systems

  • Design, implement, and analyse A/B tests at scale

  • Build ranking models using ML / deep learning techniques

  • Experiment with embeddings, candidate generation, and re-ranking strategies

  • Perform large-scale data wrangling and feature engineering

  • Conduct offline model evaluation and performance benchmarking

  • Contribute to production pipelines using Airflow and AWS services

  • Support monitoring, debugging, and optimisation of deployed ML systems

  • Adopt AI in the workflows above

You will gain exposure to real-world challenges such as:

  • Cold-start problems

  • Personalisation at scale

  • Revenue-driven model optimisation

  • Latency and infrastructure constraints in production ML systems

Learning Outcome

 

You will:

  • Understand and execute the end-to-end ML lifecycle
    (Data → Feature Engineering → Model Training → Offline Evaluation → A/B Testing → Model Deployment → Model Monitoring)

  • Design statistically sound A/B experiments and interpret business impact

  • Apply recommender system techniques in a real production environment

  • Write clean, production-ready Python and SQL code

  • Build scalable cloud-native ML pipelines

  • Gain hands-on experience with experimentation-driven product development

 

You will leave with practical experience building AI systems that directly influence revenue.

 

Pre-requisites:

  • Passion and interest in using Data Science to drive business impact.

  • Strong foundational understanding of ML fundamentals and core concepts / architectures.

  • Have hands-on ML project experience (academic or industry)

  • Proficiency in Python, SQL and experience with common machine learning frameworks (e.g. TensorFlow, Keras, Sklearn, Pytorch) and LLM-powered workflows and embeddings

  • Diligent, reliable, strong analytical skills, good communication skills, and teamwork

Experience with cloud technologies (Amazon Web Services, Google Cloud Platform)

Pre-Requisites :

Razer is proud to be an Equal Opportunity Employer. We believe that diverse teams drive better ideas, better products, and a stronger culture. We are committed to providing an inclusive, respectful, and fair workplace for every employee across all the countries we operate in. We do not discriminate on the basis of race, ethnicity, colour, nationality, ancestry, religion, age, sex, sexual orientation, gender identity or expression, disability, marital status, or any other characteristic protected under local laws. Where needed, we provide reasonable accommodations - including for disability or religious practices - to ensure every team member can perform and contribute at their best.

Are you game?


Job Requirements


Company Benefits

Career advancement

With fifteen offices and three R&D labs worldwide, be part of a global team that transcends time zones and geographical boundaries.

Transparency

You get to enjoy working in an environment that values transparency and collaborative effort.

Global exposure

You'll be at the forefront of the most exciting industry in the world—video games, bringing gamers closer to the games they love.


Additional Info

Experience Level

#NoExperienceNeeded

Job Specialisation


Company Profile

Razer Inc.-logo-image

Razer Inc.

Razer™ is the world’s leading lifestyle brand for gamers.  The triple-headed snake trademark of Razer is one of the most recognized logos in the global gaming and esports communities. With a fan base that spans every continent, the company has designed and built the world’s largest gamer-focused ecosystem of hardware, software and services. Founded in 2005, Razer is dual headquartered in Irvine (California) and...
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