Data Scientist II

About Scribd, Inc.

Scribd, Inc. strives to enhance human comprehension through its four main products—Scribd®, Slideshare®, Everand™, and Fable—serving billions worldwide by transforming access into insight, application, and expertise.

Culture and Approach

Scribd fosters an environment where authenticity and boldness drive success. Employees engage openly in debate, adapt to change, and take ownership with a strong customer focus. Their "Scribd Flex" program balances flexibility with meaningful in-person collaboration, requiring occasional office presence regardless of location. The company hires individuals embodying "GRIT," emphasizing goal setting, results delivery, innovation, and teamwork.

Team Overview

The Applied Research team specializes in deploying machine learning, NLP, and generative AI to develop impactful solutions. Collaborating with product and engineering teams, they innovate in areas like content enrichment, representation learning, recommendations, search, and translation across text, image, and audio data at massive scale.

Role Summary

This role seeks a Data Scientist II experienced in designing, developing, and deploying machine learning models. The position demands collaboration with ML engineers, data engineers, and product teams to create high-impact AI systems, emphasizing simplicity, full lifecycle visibility, and scalability.

Key Responsibilities

• Develop content classification solutions using traditional NLP, LLMs, and generative models.
• Address complex challenges at scale within Scribd’s ecosystem.
• Collaborate cross-functionally with data scientists, ML engineers, and data engineers.
• Apply diverse algorithms ranging from classical models (Scikit-learn, NumPy) to custom neural networks (PyTorch) and third-party LLM APIs.
• Process extensive datasets using Python, SQL, and Spark.
• Communicate technical approaches and outcomes effectively through documentation and stakeholder engagement.

Candidate Requirements

• Minimum of 3 years post-qualification experience developing and deploying scalable machine learning models.
• Proficiency in Python programming.
• Hands-on experience with ML pipeline construction and distributed data processing tools such as Apache Spark or Databricks.
• Intermediate expertise in at least three of these areas: classification algorithms, NLP, search, information retrieval, named entity recognition, deep learning, generative modeling.
• Intermediate or higher skills in SQL or PySpark.
• Bachelor's or Master’s degree in a relevant quantitative field (e.g., Statistics, Computer Science, Data Science, AI).

Compensation and Benefits

Salary ranges depend on geographic location and experience: in Canada, expected compensation spans from CAD 123,000 to CAD 150,000. The role offers competitive equity ownership and a comprehensive benefits package, including:

• Flexible work arrangements (Scribd Flex).
• Medical, dental, and vision coverage.
• Mental health and disability support.
• Generous paid time off encompassing vacation, sick days, holidays, winter break, volunteer days, and sabbaticals.
• Paid parental leave and family support benefits.
• Retirement matching and participation in equity programs.
• Professional development and learning opportunities.
• Wellness and home office stipends.
• Access to Scribd’s suite of products and AI tools.

Location Requirements

Candidates must reside in or near specified cities where Scribd can employ them, including Vancouver in Canada.

Diversity and Accommodations

Scribd is committed to equal opportunity employment and encourages diverse applicants. Accommodations for the interview process are available upon request.