Data Science Team Lead

Description

Rakuten Viber is one of the most popular and downloaded apps in the world. Working with us provides a unique opportunity to influence hundreds of millions of our users and to be part of the journey that makes us a super-app. Our mission is to make people’s lives easier by enabling meaningful connections, from precious moments with family and friends, through managing business relationships to pursuing their passions. 

Connecting people across the world is a complex problem with many machine-learning applications. The purpose of this role is to implement mathematical models and algorithms to solve complex business problems. Successful outcomes will significantly impact our hundreds of millions of daily active users around the globe.

As a Data Science Team Lead your leadership and expertise will progress our AI vision and strategy. This role demands a strong background in mathematics and statistics. You will work in a highly collaborative environment with extensive amounts of data to research and develop deep learning models to solve real-world problems at a high s

Responsibilities

• Be a technical leader of data scientists, with substantial scope, impact, and visibility. Mentoring and providing guidance and support to foster their growth and success. 
• Work with management and partner teams to design and implement key results for the company’s most strategic initiatives.
• Own the full data science lifecycle, including problem definition, data collection, model development, evaluation, deployment, and monitoring. 
• Autonomously find solutions to complex data science problems, with potentially non-trivial solutions, and understand the data generation process and challenges with the data.

Requirements

• Master’s degree in Statistics, Mathematics, or Computer Science.
• 5+ years managing a high-performing team of scientists and deploying production-level deep learning models with a proven business impact at scale.
• Proven ability to conduct rigorous analysis and communicate conclusions to both technical and non-technical audiences.
• Strong programming skills in Python with hands-on experience with deep learning tools such as PyTorch.
• Fluency in SQL, preferably querying from a data lake.
• Hands-on ability to read AI research publications and implement the algorithms & architectures from scratch.

Advantages

• Publication in peer-reviewed conferences or journals on reinforcement learning, deep learning, and machine learning.
• Presented your work in conferences or relevant meet-ups.
• Worked with data at a scale of 100’s of PB. Trained and deployed Gen-AI models at scale.
• Experience working with technologies like Spark, SageMaker, Athena/Trino, Milvus, and OpenSearch.

Skills