Data Scientist II
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Key skills for this role
About the Role
Scribd, Inc. seeks a Data Scientist II to develop and deploy machine learning models for content classification, search, and recommendations. You will work with massive datasets using Python, SQL, and Spark, collaborating with cross-functional teams.
Key Skills for This Role
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.
- Bachelors or Masters in relevant quantitative discipline including but not limited to Statistics, Computer Science, Data Science, Artificial Intelligence or another field with a strong quantitative focus.
Full Job Posting
About The Team
- The Applied Research team is a group of data scientists and content specialists who are experts in leveraging machine learning, natural language processing and generative AI models.
- We act as a key driver for innovation, whether it’s in product surface experimentation, metadata generation or model development.
- Our areas of impact include content enrichment, representation learning, recommendations, search, translation and many others, applied to diverse media across text, image, and audio.
Role Overview
- We are seeking a Data Scientist II with experience developing and deploying machine learning models.
- You will help design and implement high impact AI and ML systems.
- We work in cross functional teams collaborating with Machine Learning Engineers, Data Engineers and Product.
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.
- Bachelors or Masters in relevant quantitative discipline including but not limited to Statistics, Computer Science, Data Science, Artificial Intelligence or another field with a strong quantitative focus.
Compensation
- In Canada, the reasonably expected salary range is between CAD 123,000 to CAD 150,000.
- This position is also eligible for a competitive equity ownership, and a comprehensive and generous benefits package.
Benefits At Scribd, Inc.
- 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
- Retirement 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
Working at Scribd, Inc.
- Scribd Flex empowers employees to choose the workstyle and location that support their best performance, while committing to intentional in person moments that strengthen collaboration and culture.
- Occasional in person attendance is required for all Scribd, Inc. employees, regardless of location.
- Employees must have their primary residence in or near one of the following cities: Ottawa, Toronto, Vancouver (Canada).
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