Data Scientist II - ML & NLP at Scale

Scribd, Inc.; San Diego (CA); Hybrid; USD 118,000 - 184,000; Full time

Benefits offered by this job

Scribd Flex (flexible work model)

Comprehensive health, dental, and vis

Paid time off and holidays

Parental leave and family support

Job summary

Scribd, Inc. is seeking a Data Scientist II to design and deploy high-impact ML systems within the Applied Research team. You will work with Machine Learning Engineers, Data Engineers, and Product partners to build scalable models for content classification, translation, and recommendations.

You will handle large datasets using Python, SQL, and Spark, and apply NLP, deep learning, and generative models. Strong collaboration and clear documentation are essential to drive business impact.

Qualifications

• 3+ years of post-qualification experience developing ML models at scale.
• Proficiency in Python.
• Experience building ML pipelines with distributed frameworks such as Spark/Databricks.

Responsibilities

• Focus on content classification use cases, leveraging NLP, LLMs and generative models.
• Investigate scalable methods to solve Scribd's challenges at scale.
• Collaborate with Data Scientists, ML Engineers and ML Data Engineers on cross-functional projects.
• Leverage algorithms from traditional ML to PyTorch and third-party LLM APIs.
• Process massive data with Python, SQL and Spark.
• Communicate approaches and results to stakeholders with detailed documentation.

Skills

Python

Spark

NLP

SQL

Deep Learning

Generative Models

Information Retrieval

ML Pipelines

Education

Bachelor's or Master's in quantitative discipline

Tools

Apache Spark

Databricks

Scikit-Learn

NumPy

PyTorch

Job description

Scribd, Inc. is seeking a Data Scientist II to design and deploy high-impact ML systems within the Applied Research team. You will work with Machine Learning Engineers, Data Engineers, and Product partners to build scalable models for content classification, translation, and recommendations.

You will handle large datasets using Python, SQL, and Spark, and apply NLP, deep learning, and generative models. Strong collaboration and clear documentation are essential to drive business impact.