Data Scientist II

Overview

Data Scientist II role at Scribd, Inc.

About the company: At Scribd (pronounced “scribbed”), our mission is to spark human curiosity. We aim to democratize the exchange of ideas and information and empower collective expertise through our products: Everand, Scribd, and Slideshare.

About The Team

The Applied Research team is a group of data scientists and content specialists who leverage machine learning, natural language processing and generative AI models to develop value-driven solutions. We collaborate with Product and Engineering partners in cross-functional squads to maximize business impact across content enrichment, representation learning, recommendations, search, translation, and more, at scale (hundreds of millions of documents, millions of users, billions of interactions).

Role Overview

We are seeking a Data Scientist II with experience developing and deploying machine learning models. You will design and implement high impact AI and ML systems in a cross-functional setting with Machine Learning Engineers, Data Engineers and Product. A curious, collaborative mindset with focus on simplicity, end-to-end visibility and impact is required. You will build models using large-scale data and language models, and deploy them.

Responsibilities

Focus on content classification use cases, leveraging traditional NLP, LLMs and generative models

Investigate scalable methods to solve challenging problems at Scribd

Collaborate with Data Scientists, ML Engineers and ML Data Engineers on cross-functional projects

Use a range of algorithms from classical Scikit-learn/NumPy to PyTorch neural networks and third-party LLM APIs

Process large datasets with Python, SQL and Spark

Communicate approaches and results clearly to stakeholders and maintain detailed project documentation

Requirements

3+ years of post-qualification experience developing ML models, working with systems at scale and deploying to production

Proficiency in Python

Hands-on experience building ML pipelines and with distributed data processing frameworks (e.g., Apache Spark, Databricks)

Intermediate level in at least three of: classification algorithms, NLP, search, information retrieval, named entity recognition, deep learning, generative models

Intermediate level or greater experience with SQL or PySpark

Bachelor’s or Master’s in a quantitative field (Statistics, Computer Science, Data Science, AI, etc.)

Compensation and Benefits

Base pay is determined within a range based on location and market benchmarks. Salary ranges vary by geography and level. This position is eligible for a competitive equity package and a comprehensive benefits program. See company policy for specifics.

Working at Scribd

Employees must have their primary residence within or near listed cities in the United States, Canada, or Mexico, with occasional in-person attendance as part of Scribd Flex. Scribd is committed to equal employment opportunity and values diverse perspectives.

Next Steps

Referrals increase your chances of interviewing. If you are based in or near Toronto, Ontario, Canada or other listed locations, you may be eligible for roles in the region. #J-18808-Ljbffr