Data Scientist II: ML & NLP at Scale

Scribd, Inc.; Washington (District of Columbia); On-site; USD 97,000 - 175,000; Full time

Benefits offered by this job

Scribd Flex

Health coverage

PTO & holidays

Parental leave

Retirement matching

Learning & development

Job summary

Scribd, Inc. is seeking a Data Scientist II to design and deploy ML systems for content classification and NLP tasks at scale. You will work with ML Engineers, Data Engineers and Product teams to deliver end‑to‑end AI solutions using massive data and language models.

The role requires 3+ years of production ML experience, Python fluency and expertise in Spark or Databricks, with a track record of delivering impactful models and clear stakeholder communication.

Qualifications

• 3+ years of post‑qualification experience developing ML models, scaling systems and deploying to production.
• Proficiency in Python.
• Hands‑on experience building ML pipelines and with distributed data processing frameworks (e.g., Spark, Databricks).
• Fluency in at least three areas: classification, NLP, search, information retrieval, NER, DL, or generative models.
• Experience with SQL or PySpark.
• Degree in Statistics, Computer Science, Data Science, AI or similar quantitative field.

Responsibilities

• Develop and deploy ML models for content classification and related NLP tasks.
• Collaborate with Data Scientists, ML Engineers and Product on cross‑functional projects.
• Experiment with classical methods, PyTorch networks and third‑party LLM APIs.
• Process large data with Python, SQL and Spark.
• Document approaches and results clearly for stakeholders.

Skills

Python

Spark/Databricks

NLP

SQL

Education

Bachelor's or Master's in quantitative field

Job description

Scribd, Inc. is seeking a Data Scientist II to design and deploy ML systems for content classification and NLP tasks at scale. You will work with ML Engineers, Data Engineers and Product teams to deliver end‑to‑end AI solutions using massive data and language models.

The role requires 3+ years of production ML experience, Python fluency and expertise in Spark or Databricks, with a track record of delivering impactful models and clear stakeholder communication.