Data Scientist II

About the role

The Applied Research team at Scribd, Inc. is seeking a Data Scientist II to develop and deploy machine learning models. This role focuses on content classification use cases, working with large datasets, and collaborating with cross-functional teams.

Responsibilities

• Focus on a variety of content classification use cases, leveraging everything from traditional NLP to sophisticated LLMs and generative models
• Investigate methods of solving our most challenging problems at Scribd, at scale
• Collaborate with other Data Scientists, Machine Learning Engineers, and ML Data Engineers on cross-functional projects
• Leverage any algorithm at your disposal: from classical Scikit-learn and NumPy models to custom Neural Networks in PyTorch to third party LLM APIs
• Process massive amounts of data with Python, SQL, and Spark
• Align with stakeholders through written and verbal communications methods on the approaches and results of projects, while writing detailed, accurate, and concise project documentation

Requirements

• 3+ years of post qualification experience developing machine learning models, working with systems at scale and deploying to production environments
• Proficiency in Python
• Hands-on experience building ML pipelines and working with distributed data processing frameworks like Apache Spark, Databricks, or similar
• Intermediate level in at least three of these fields: classification algorithms, natural language processing, 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 relevant quantitative discipline including but not limited to Statistics, Computer Science, Data Science, Artificial Intelligence, or another field with a strong quantitative focus

Qualifications

• Experience with machine learning models and systems at scale
• Hands-on experience with Python and distributed data processing frameworks
• Intermediate to advanced knowledge in at least three of the following areas: classification algorithms, natural language processing, search, information retrieval, named entity recognition, deep learning, generative models
• Intermediate to advanced SQL or PySpark skills
• Relevant education or training in a quantitative discipline such as Statistics, Computer Science, Data Science, Artificial Intelligence, or another field with a strong quantitative focus

Skills

• Strong problem-solving and analytical skills
• Ability to work independently and collaboratively in a fast-paced environment
• Experience with large-scale data processing and analysis
• Knowledge of machine learning algorithms and techniques
• Experience with natural language processing and generative models

Benefits

• Scribd Flex (flexible work model)
• Comprehensive health, dental, and vision coverage
• Mental health support and disability coverage
• Generous paid time off, including vacation, sick time, holidays, winter break, volunteer time, and sabbaticals
• Paid parental leave and family support benefits
• Retailment matching and employee equity
• Learning and development programs and professional growth opportunities
• Wellness and home office stipends
• Complimentary access to the Scribd, Inc. suite of products
• Enterprise access to leading AI tools