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 #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 systemsDesign, implement, and analyse A/B tests at scaleBuild ranking models using ML / deep learning techniquesExperiment with embeddings, candidate generation, and re-ranking strategiesPerform large-scale data wrangling and feature engineeringConduct offline model evaluation and performance benchmarkingContribute to production pipelines using Airflow and AWS servicesSupport monitoring, debugging, and optimisation of deployed ML systemsAdopt AI in the workflows aboveYou will gain exposure to real-world challenges such as:Cold-start problemsPersonalisation at scaleRevenue-driven model optimisationLatency and infrastructure constraints in production ML systemsLearning 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 impactApply recommender system techniques in a real production environmentWrite clean, production-ready Python and SQL codeBuild scalable cloud-native ML pipelinesGain 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 embeddingsDiligent, reliable, strong analytical skills, good communication skills, and teamworkExperience 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?