Data Scientist I

Toronto OR Remote Canada

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At Scribd (pronounced “scribbed”), we believe reading is more important than ever. Join our cast of characters as we work to change the way the world reads by building the world’s largest and most fascinating digital library: giving subscribers access to a growing collection of ebooks, audiobooks, magazines, documents, Scribd Originals, and more. In addition to works from major publishers and top authors, our community includes over 1.5M subscribers in nearly every country worldwide.
About the team:Applied Research Content Modeling is a team of data scientists who extract quantitative understanding from the complex unstructured data in our growing corpus of varied multi-modal content. We are a world class AI/ML organization whose mission is to break new ground in how our customers discover content. 
We are skilled in employing a diversity of methods from metadata extraction, natural language processing, computer vision, to classification. We build the rich semantic connections between our content and our users. We strive to know our users better than they know themselves, enabling us to transform personalized discovery experiences.
We are a full-stack data science team that runs exploratory analyses, sizes business impact, creates data pipelines, presents projects, and builds models from research prototype to production system serving product features. We work on Scribd’s unique and massive dataset consisting of hundreds of millions of documents, books, audiobooks, articles, slides and podcasts. 
You will:- Build ML models in Python and Spark- Leverage state-of-the-art models using deep learning frameworks such as PyTorch and Tensorflow- Work with Senior Data Scientists to operationalize data science projects- Educate stakeholders through written and verbal communications methods on the approaches and results of projects, while writing detailed, accurate and concise project write ups- Investigate methods of solving our most challenging problems at Scribd.
You Have:- 1-2 years of experience deploying machine learning models (natural language processing experience preferred) - Beginner level or greater experience with SQL and Spark- Intermediate to advanced knowledge with Python- Intermediate level in at least one of these fields: natural language processing, deep learning, computer vision, and bayesian or frequentist statistics- A keen interest in learning what’s necessary to solve a business problem and make a positive business impact.- Bachelors or Masters in relevant quantitative discipline (e.g. Computer Science, Software Engineering, Data Science, Machine Learning, Artificial Intelligence, Computational Linguistics, Mathematics, Statistics)Benefits, Perks, and Wellbeing at Scribd
• Healthcare Benefits: Scribd pays 100% of employee’s Medical, Vision, and Dental premiums and 70% of dependents• Leaves: Paid parental leave, 100% company paid short-term/long-term disability plans and milestone Sabbaticals• 401k plan through Fidelity, plus company matching with no vesting period• Equity - Every employee is an owner in Scribd! • Generous Paid Time Off, Paid Holidays, Flexible Sick Time, Volunteer Day + office closure between Christmas Eve and New Years Day• Referral bonuses• Professional development: generous annual budget for our employees to attend conferences, classes, and other events• Company-wide Diversity, Equity, & Inclusion programs which include learning & development opportunities, employee resource groups, and hiring best practices.• Learning & Development and Coaching programs• Monthly Wellness, Connectivity & Comfort Benefit• Concern mental health digital platform• Work-life balance flexibility• Company events + Scribdchats• Free subscription to Scribd + gift memberships for friends & family
Want to learn more? Check out our office and meet some of the team at
Scribd is committed to equal employment opportunity regardless of race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.
We encourage people of all backgrounds to apply. We believe that a diversity of perspectives and experiences create a foundation for the best ideas. Come join us in building something meaningful.
Job region(s): North America
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