Data Scientist, Scribd

$97-184k

+ Equity. Salary dependent on location. In Canada, the reasonably expected salary range is between $123,000 CAD to $150,000 CAD

SQL

Python

Spark

NumPy

Scikit-Learn

PyTorch

Mid and Senior level

Remote from Canada, US

More information about location

E-book and audiobook subscription service

Be an early applicant

E-book and audiobook subscription service

201-500 employees

B2CLearningEntertainmentSocial

Be an early applicant

$97-184k

+ Equity. Salary dependent on location. In Canada, the reasonably expected salary range is between $123,000 CAD to $150,000 CAD

SQL

Python

Spark

NumPy

Scikit-Learn

PyTorch

Mid and Senior level

Remote from Canada, US

More information about location

201-500 employees

B2CLearningEntertainmentSocial

Company mission

To revolutionize the way the world reads and learns.

Job

Company

Role

Who you are

We are seeking a Data Scientist II with experience developing and deploying machine learning models
We are seeking a curious and collaborative individual with an eye for simplicity, end-end visibility and impact and that is excited about building models using massive amounts of data, using language models and deploying models
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

What the job involves

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
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

Our take

The world's biggest site for social reading and publishing, Scribd's website has over 250 million unique visitors each month and a vast content library, consisting of over 200 million audiobooks, magazines, ebooks and newspapers as well as media created by the Scribd community.

While Scribd is the largest social reading site, it is not alone in offering this kind of media. It competes against some major players, the largest of which are Amazon's Kindle and Audible offerings, but also includes the likes of BookMate and the non-profit Internet Archive. Where it stands aside is in its feature-rich reader and the sheer diversity of its library, which, thanks to partnerships with several major publishers, features numerous popular titles as well as a range of independent creators.

Further differentiating it from competitors, the company taken a firm stand on social issues, in particular the recent wave of book bannings taking place across the United States. By making the banned titles freely available it hopes to do its part in preserving literary freedom. With this tendency showing no signs of slowing down, Scribd's intervention in this area could prove to be important.

Kirsty

Company Specialist at Welcome to the Jungle

Insights

Top investors

0% employee growth in 12 months

Glassdoor (3)

Trustpilot (1.2)

Company

Funding (last 2 of 7 rounds)

Nov 2019

$58m

LATE VC

Jan 2015

$22m

LATE VC

Total funding: $105.9m

Company benefits

Healthcare Insurance Coverage (Medical/Dental/Vision): 100% paid for employees
12 weeks paid parental leave
Short-term/long-term disability plans
401k/RSP matching
Tuition Reimbursement
Learning & Development programs
Quarterly stipend for Wellness, Connectivity & Comfort
Mental Health support & resources
Free subscription to Scribd + gift memberships for friends & family
Referral Bonuses
Book Benefit
Sabbaticals
Company wide events
Team engagement budgets
Vacation & Personal Days
Paid Holidays (+ winter break)
Flexible Sick Time
Volunteer Day
Company-wide Diversity, Equity, & Inclusion programs

Company HQ

China Basin, San Francisco, CA

Leadership

Tony Grimminck

(CEO)

Joined the company in 2019 as CFO, becoming CEO in 2023. Previously co-founded International Connector, has served as Board Member and Advisor at various companies, and was CFO at Oto Analytics.

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