Data Scientist Intern

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 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?