The role involves working in a team focused on applied research, where data scientists leverage machine learning models and natural language processing to create solutions that benefit users and the business.
The team collaborates with product and engineering partners, and they focus on various areas such as content classification, recommendations, and search.
By operationalizing data projects, the role contributes to innovation and impact at scale. The position emphasizes building models that can influence millions of users.
Required Qualifications and Skills
The role requires 2-3 years of experience in developing and deploying machine learning models, along with intermediate to advanced knowledge of Python and experience with SQL or Spark.
Candidates should be proficient in classification algorithms and natural language processing among other areas. A Bachelor's or Master's degree in a relevant quantitative field is necessary.
The applicant should possess a keen interest in solving business problems and making a positive impact.
Scribd, self-described as a platform designed to spark human curiosity, champions a paradigm for exchanging ideas and empowering collective expertise through its array of products including Everand, Scribd, and Slideshare.
It fosters a dynamic workplace culture centered on authenticity, enthusiasm for collaborative problem-solving, and the flexibility to cater to individual work style preferences through the Scribd Flex benefit.
This approach underpins its mission to enrich lives with a trove of stories and knowledge, administered on a robust digital platform that prioritizes customer-centric innovation and connection.
At its core, Scribd employs AI and advanced data analytics to refine user experiences and subscription models, reflecting its commitment to accessibility and the democratization of information.
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