Data Scientist II
- Canada
Full-time
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Job details
- Job type
- Full-time
- Experience
- 3+ years of post-qualification experience developing machine learning models at scale and deploying them into production environments.
- Posting language
- English
- Posted
Original job description
Scribd, Inc. is a pioneering platform dedicated to advancing human understanding through innovative digital content solutions. Our mission is to help billions of people worldwide move beyond mere access to information and into the realms of insight, application, and expertise. Our portfolio includes four flagship products: Scribd®, Slideshare®, Everand™, and Fable, each designed to cater to diverse user needs across various media formats. We foster a dynamic and inclusive culture that encourages employees to be authentic, bold, and collaborative. At Scribd, Inc., we believe that the best work emerges when individual flexibility is balanced with meaningful community engagement. Our Scribd Flex work model empowers employees to choose their optimal workstyle and location, while also emphasizing the importance of in-person interactions to strengthen team cohesion and company culture. We are committed to diversity, equity, and inclusion, welcoming talent from all backgrounds to join us in our journey of innovation and growth.
About The Role
We are seeking a highly skilled Data Scientist II to join our Applied Research team, a group of experts in leveraging machine learning, natural language processing, and generative AI models. In this role, you will be instrumental in designing, developing, and deploying high-impact AI and ML systems that deliver tangible value to our users and business operations. You will collaborate closely with cross-functional teams including Machine Learning Engineers, Data Engineers, and Product Managers to create scalable solutions across content enrichment, recommendation systems, search, translation, and more. Your work will involve handling vast datasets, utilizing advanced language models, and deploying models that operate at scale. The ideal candidate will be curious, innovative, and passionate about building impactful models using large datasets, with a focus on simplicity, transparency, and end-to-end impact. This position offers an exciting opportunity to work on cutting-edge AI projects that influence millions of users worldwide.
Qualifications
- 3+ years of post-qualification experience developing machine learning models at scale and deploying them into production environments.
- Proficiency in Python programming language.
- Hands-on experience building ML pipelines and working with distributed data processing frameworks such as Apache Spark, Databricks, or similar.
- Intermediate expertise in at least three of the following fields: classification algorithms, natural language processing, search, information retrieval, named entity recognition, deep learning, generative models.
- Intermediate or higher proficiency with SQL or PySpark.
- Bachelor’s or Master’s degree in a relevant quantitative discipline, including Statistics, Computer Science, Data Science, Artificial Intelligence, or related fields with a strong quantitative focus.
- Experience working with classical machine learning algorithms, neural networks, and third-party language model APIs.
- Strong analytical skills with the ability to process and interpret large datasets effectively.
- Excellent communication skills, capable of articulating complex technical concepts to diverse stakeholders.
- Design and develop machine learning models for various content classification use cases, utilizing traditional NLP techniques, large language models, and generative AI.
- Investigate and implement innovative solutions to complex challenges at scale within Scribd’s ecosystem.
- Collaborate with Data Scientists, Machine Learning Engineers, Data Engineers, and Product teams to develop integrated solutions that maximize business impact.
- Leverage a variety of algorithms and frameworks, including Scikit-learn, PyTorch, and third-party API integrations, to build and refine models.
- Process and analyze large-scale datasets using Python, SQL, Spark, and other distributed data processing tools.
- Document project approaches, methodologies, and results clearly and concisely for technical and non-technical audiences.
- Engage with stakeholders to align project goals, deliverables, and timelines effectively.
- Continuously monitor, evaluate, and improve model performance to ensure accuracy and relevance.
- Flexible work arrangements through Scribd Flex, supporting work-life balance.
- Comprehensive health, dental, and vision insurance coverage.
- Mental health support and disability coverage programs.
- Generous paid time off, including vacation, sick leave, holidays, winter break, volunteer days, and sabbaticals.
- Paid parental leave and family support benefits.
- Retirement matching programs and opportunities for employee equity ownership.
- Access to learning and professional development programs for career growth.
- Wellness stipends and home office setup allowances.
- Complimentary access to Scribd’s products and enterprise-level AI tools.
Scribd, Inc. is an equal employment opportunity employer. We are committed to creating a diverse and inclusive environment where all employees and applicants are treated with respect and fairness, regardless of race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability, or any other characteristic protected by law. We encourage individuals from all backgrounds to apply and contribute to our mission of fostering innovation and understanding through technology.
More about this job
Responsibilities
Design, develop, deploy, and improve machine learning models for content classification and other applications, using NLP, generative AI, and large-scale data processing tools. Collaborate with technical and product teams, communicate project methods and results, and align solutions with stakeholder goals.
Requirements
Requires at least three years of experience developing and deploying machine learning models at scale, proficiency in Python, and hands-on experience with ML pipelines and distributed data processing. Candidates should have a relevant quantitative bachelor's or master's degree, expertise in at least three specified ML fields, and experience with classical ML, neural networks, and language model APIs.
Skills
- Machine Learning
- Python
- SQL
- PySpark
- Apache Spark
- Databricks
- Natural Language Processing
- Classification Algorithms
- Search
- Information Retrieval
- Named Entity Recognition
- Deep Learning
- Generative AI
- Scikit-learn
- PyTorch
- Large Language Models
Benefits
- Flexible Work Arrangements
- Health Insurance
- Dental Insurance
- Vision Insurance
- Mental Health Support
- Disability Coverage
- Paid Time Off
- Paid Parental Leave
- Retirement Matching
- Employee Equity
- Professional Development
- Wellness Stipend
- Home Office Allowance
- Complimentary Product Access
- AI Tools Access
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Science & Research
- Software
Keywords
- Machine Learning
- Applied Research
- Artificial Intelligence
- Natural Language Processing
- Generative AI
- Large Language Models
- Content Classification
- Recommendation Systems
- Search
- Information Retrieval
- Named Entity Recognition
- Deep Learning
- Classification Algorithms
- Python
- SQL
- PySpark
- Apache Spark
- Databricks
- Machine Learning Pipelines
- Scikit-learn
- PyTorch
- Third-Party Language Model APIs
- Distributed Data Processing
- Model Deployment
- Model Performance Monitoring
- Data Analysis
- Statistics
- Data Science
- Computer Science