About the job
About Crunchyroll
Founded by enthusiasts, Crunchyroll brings the vibrant art and culture of anime to a dedicated community. We cater to over 100 million anime and manga fans spanning more than 200 countries and territories, connecting them to the stories and characters they cherish. Whether through streaming video, theatrical releases, games, merchandise, or events, our platform is powered by the beloved anime content we all enjoy.
Become a part of our team and help us define the future of anime!
About the Role
We are seeking a Manager of Machine Learning and Data Science in the Hyderabad area to lead and expand a team utilizing advanced Data Science and Machine Learning techniques for our global digital entertainment platform. Our ecosystem includes paid VOD streaming, online Manga reading, Merchandising, Gaming, and Music Video experiences, all centered around enhancing user engagement and premium content consumption within the anime community.
In this position, you will oversee a team of Machine Learning Engineers and Data Scientists who are dedicated to analyzing content, user behavior, and product engagement. You will transform these insights into actionable business strategies and product features that provide personalized user experiences. Collaborating closely with the Director of Data Science & Machine Learning (DSML), you will scale both the team and the technical capabilities necessary to support our expanding multi-product platform.
This role is perfect for a leader who possesses a blend of strong technical acumen and people management skills, guiding teams from exploratory analysis to the deployment of production-ready ML systems that directly enhance customer experience and drive business success.
Core Areas of Responsibility
- Lead, mentor, and develop a team of Machine Learning Engineers and Data Scientists, fostering a culture of technical excellence and accountability.
- Drive the delivery of ML and analytics initiatives aimed at improving content discovery, personalization, user engagement, and cross-platform experiences.
- Provide technical guidance on modeling approaches, experimentation, and production readiness to ensure scalable and dependable solutions.
- Translate business objectives into clear ML roadmaps in partnership with Product, Engineering, and business stakeholders.
- Ensure that insights and model outputs are communicated effectively to inform strategic and operational decisions.
- Establish and standardize best practices across experimental methodologies.

