Data Science 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 :

Intern will be playing a key role in supporting to building & optimizing of Artificial Intelligence (AI) / Machine Learning (ML) Engines, that are important to Razer’s AI initiatives.

The intern will work on revamping existing feature pipelines and building of new feature pipelines via feature engineering efforts. The intern can also be involved in the deployment of models via a systematic MLOps pipeline. By analyzing the output of the deployed models, the intern will also perform further analysis to better improve the models. Throughout the process, the intern will learn the skills of proper documentation for these works.

Requirements:

• Creative and innovative mindset and ability to work independently

• Ability to use one or more development language (Python, SQL, Dbt, etc)

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

• Familiar with orchestration tools.

• Interest and experience in Data Science, Machine Learning and Artificial Intelligence

Learning Objectives

The intern can learn data science concept, feature engineering skills, deployment of AI/ML models systematically via MLOps and understand the wider realm of data science. The application of the different cloud computing knowledge can also be picked up.

Learning Outcome

• Industry practices and essentials to writing clean code in Python

• Industry usage of a proper CI/CD for code repository integration and deployment

• Feature engineering, including pipeline design and boiler plating

• Algorithm selection and AI/ML model training

• AI/ML model evaluation techniques

• Cloud computing technology – AWS

• Infrastructure as code - Terraform

• Technical requirement gathering and translation

Pre-Requisites :

Are you game?