Data Scientist II

About Scribd, Inc.

Scribd, Inc. empowers billions of users globally through our platforms: Scribd®, Slideshare®, Everand™, and Fable. Our mission is to foster deeper understanding by transforming access into actionable insights and expertise. Within our culture, we highly value authenticity, boldness, and a collaborative approach, supporting both flexible work arrangements and intentional in-person collaboration.

Our Team and Approach

The Applied Research group drives innovation at Scribd, Inc. by combining expertise in machine learning, natural language processing, and generative AI. We partner with engineering and product teams to design advanced solutions in areas such as content classification, metadata enrichment, recommendations, and search — all at massive scale, impacting millions of users and billions of data points across diverse media types (text, audio, image).

Role Overview

As a Data Scientist II, you will architect, develop, and deploy state-of-the-art AI systems to solve high-impact business problems. This position involves deep collaboration with ML Engineers and Data Engineers, focusing on leveraging large datasets and advanced language models to build and operationalize robust models. We're looking for someone who brings curiosity, teamwork, and a drive for impactful simplicity.

Key Responsibilities

• Design and optimize content classification systems, utilizing both classic NLP and the latest large language models (LLMs) and generative techniques.
• Pursue scalable solutions to complex, data-driven challenges.
• Collaborate on cross-functional projects with fellow data scientists and engineers.
• Select and apply a wide range of algorithms, leveraging Scikit-learn, NumPy, PyTorch, and external LLM APIs as appropriate.
• Implement large-scale data processing using Python, SQL, and Apache Spark environments.
• Communicate project approaches and outcomes clearly to stakeholders, and produce thorough technical documentation.

Requirements

• At least 3 years of professional experience building and deploying machine learning models in production, working with high-volume systems.
• Advanced skills in Python.
• Direct experience developing ML pipelines and using distributed data processing tools such as Apache Spark or Databricks.
• Proficient in three or more of the following areas: classification methods, NLP, search technologies, information retrieval, named entity recognition, deep learning, or generative model development.
• Intermediate or higher expertise with SQL or PySpark.
• Bachelor's or Master’s degree in a quantitative discipline such as Statistics, Computer Science, Data Science, AI, or a similar field.

Compensation and Benefits

• Canadian base salary typically ranges from 123,000 to 150,000 CAD, determined by location, experience, and qualifications.
• Competitive equity participation and comprehensive benefits including flexible work model (Scribd Flex), full health/dental/vision coverage, mental health resources, substantial paid leave (including vacation, sick days, holidays, sabbaticals, etc.), paid parental leave, retirement plan with matching, professional development, home office stipends, and more.
• Complimentary access to all Scribd, Inc. products and AI tools.

Additional Information

• Primary residence must be near one of the hiring metro areas (e.g., Ottawa, Toronto, Vancouver for Canada).
• Scribd, Inc. encourages applications from candidates of all backgrounds, upholding an inclusive and equal opportunity workplace.
• Adjustments for accessibility are available upon request throughout the interview process.