Data Scientist II

At Scribd (pronounced “scribbed”), our mission is to spark human curiosity. Join our team as we create a world of stories and knowledge, democratize the exchange of ideas and information, and empower collective expertise through our three products: Everand, Scribd, and Slideshare. 
We support a culture where our employees can be real and be bold; where we debate and commit as we embrace plot twists; and where every employee is empowered to take action as we prioritize the customer.
Our flexible work benefit - Scribd Flex - enables employees, in partnership with their manager, to choose the daily work-style that best suits their individual needs. As an organization, we prioritize collaboration and intentional in-person moments to build culture and connection. For this reason, occasional in-person attendance is required for all Scribd employees, regardless of their location.
About the team
The Applied Research team is a group of data scientists and content specialists who are experts in leveraging machine learning models, natural language processing and generative AI to develop solutions which deliver value to our users and business.We act as a key driver for innovation, whether it’s in product surface experimentation, metadata generation or model development. Along with Product and Engineering partners, we design solutions and collaborate in cross-functional squads to maximize business impact.Our areas of impact include representation learning, recommendations, search, translation and many others, applied to diverse media across audio, image and text. We operate at a scale of hundreds of millions of documents, millions of users and billions of user interactions.

About You

• Genuinely have a love for books and enjoy reading
• Are a curious individual who enjoys exploring data and finding meaning behind its patterns
• Have a collaborative spirit and enjoy sharing knowledge with your colleagues
• Have an eye for impact and are excited to build models that will affect millions of users

Responsibilities

• In your first year, you’ll be focusing on a variety of content classification use cases, leveraging everything from traditional NLP to sophisticated fine tuning of LLMs
• Investigate methods of solving our most challenging problems at Scribd, at scale
• Work with other Data Scientists and Machine Learning Engineers to operationalize data science projects
• Leverage any algorithm at your disposal: from classical Scikit-learn and NumPy models to custom Neural Networks in PyTorch to third party LLM APIs
• Process massive amounts of data with Python, SQL and Spark
• Educate stakeholders through …