Data Scientist II: Scalable ML & NLP for Global Impact

Scribd, Inc.; Atlanta (GA); On-site; USD 97,000 - 175,000; Full time

Benefits offered by this job

Scribd Flex (flexible work model)

Health, dental, and vision coverage

Paid time off incl. vacation/sick/hols

Job summary

Scribd, Inc. is seeking a Data Scientist II to design and deploy AI/ML systems that power content understanding across our platform. You will work with ML Engineers, Data Engineers and Product teams to build scalable models using Python, Spark, and modern ML frameworks.

You will analyze large datasets, experiment with language models, and deliver end-to-end solutions with strong documentation and cross-functional collaboration. The role emphasizes impact, simplicity, and clear communication.

Qualifications

• 3+ years of post-qualification experience developing ML models at scale and deploying to production.
• Proficiency in Python.
• Hands-on experience building ML pipelines and working with distributed data processing frameworks like Apache Spark, Databricks, or similar.
• Proficiency in at least three of: classification algorithms, NLP, search, information retrieval, NER, deep learning, generative models.

Responsibilities

• Focus on content classification use cases using NLP and LLMs at scale.
• Collaborate with Data Scientists, ML Engineers and Data Engineers on cross-functional projects.
• Build and deploy ML models and pipelines using Python, Spark, and PyTorch; leverage various ML tools and APIs.
• Document approaches, results, and decisions clearly for stakeholders.

Skills

Python

Spark

SQL

NLP

Machine learning

Data analysis

Distributed systems

PyTorch/ML frameworks

Education

Bachelor's or Master's in a quantitative field

Tools

Databricks

Scikit-learn

PyTorch

Job description

Scribd, Inc. is seeking a Data Scientist II to design and deploy AI/ML systems that power content understanding across our platform. You will work with ML Engineers, Data Engineers and Product teams to build scalable models using Python, Spark, and modern ML frameworks.

You will analyze large datasets, experiment with language models, and deliver end-to-end solutions with strong documentation and cross-functional collaboration. The role emphasizes impact, simplicity, and clear communication.