Data Scientist

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 build 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 1.4M subscribers in nearly every country worldwide.
About the TeamApplied Research works on a variety of ML and NLP projects like keyphrase and entity extraction/linking, classification and clustering. We are a full-stack data science team that runs exploratory analyses, sizes business impact, creates data pipelines, presents projects, and builds models from prototype to production. We work on Scribd’s unique and massive dataset consisting of hundreds of millions of documents, books, audiobooks, articles, and podcasts.
About YouYou are a curious person who enjoys tackling hard problems. You got into data science because you love being at the forefront of what is possible and the idea of building intelligent systems that scale to reach millions of people motivates you. As a senior data scientist, you’ve refined your talent towards always creating a positive business impact. You are continuously looking out for new areas to improve your technical skills and domain expertise.

You Will:

  • Build ML models in Spark and Python.
  • Leverage state-of-the-art models using deep learning frameworks such as PyTorch or TensorFlow. 
  • Increase the effectiveness of the team on a technical and problem-solving level through thoughtful collaboration and mentorship.
  • Take complicated concepts, systems, and processes and clearly communicate what matters to stakeholders.
  • Work at a high-level with the lead or manager on desired project outcomes, team strategy, project ideation, and best practices.

You Have:

  • 3+ years of experience in data science or ml engineering.
  • BA/BS in a quantitative discipline. Master’s or Doctorate degree preferred.
  • Intermediate level or greater experience with SQL, Spark, and Python.
  • Advanced level in at least one of the following 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.
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• Diversity, Equity, & Inclusion hiring best practices• Stock Options - 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 training• Learning & Development and Coaching programs• Monthly Wellness, Connectivity & Comfort Benefit• Concern mental health digital platform• Work-life balance flexibility• Employee Resource Groups that build community and support among employees• Company events + Scribdchats• Free subscription to Scribd + gift memberships for friends & family• Monthly inclusive multi-cultural celebrations & learning opportunities
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): Remote/Anywhere North America
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