Coursera was launched in 2012 by two Stanford Computer Science professors, Andrew Ng and Daphne Koller, with a mission to provide universal access to world-class learning. It is now one of the largest online learning platforms in the world, with 92 million registered learners as of Sept. 30, 2021. Coursera partners with over 250 leading university and industry partners to offer a broad catalog of content and credentials, including Guided Projects, courses, Specializations, certificates, and bachelor’s and master’s degrees. Institutions around the world use Coursera to upskill and reskill their employees, citizens, and students in many high-demand fields, including data science, technology, and business. Coursera became a B Corp in February 2021.
At Coursera, our Data Science team is helping to build the future of education through data-powered products and data-driven decisions. In Machine Learning, we define, develop, and launch the models and algorithms that power content discovery, personalized learning, and machine-assisted teaching and grading. In Decision Science, we drive product and business strategy through measurement, experimentation, and causal inference. We believe the next generation of teaching and learning should be personalized, accessible, and efficient. With our scale, data, technology, and talent, Coursera and its Data Science team are positioned to make that vision a reality.
We are looking for a creative, collaborative, and computationally strong Data Scientist to innovate Coursera’s recommendation engine and product applications. Our recommendation engine is the key driver of delivering a personalized experience to our learners and help them find the best content that matches their learning interests. It powers a wide range of applications from on-platform recommendations to marketing emails. Our ideal candidate possesses a strong statistical and computational skill set, is collaborative and impact-driven, and shares our passion for education.
Ideate, prototype, and productionize the machine learning algorithms that power Coursera’s products, especially our recommendation engine for online degree programs (e.g., degree recruitment engine, cohort forecasting, real-time recommendation, email bandits )
Design, deploy and scale end-to-end machine learning / deep learning pipelines and models with AWS cloud services
Distill insights from complex data and/or data product results; communicate findings clearly to both technical and non-technical audiences
Partner with Product Managers and Engineers to identify and articulate opportunities, build efficient and scalable ML solutions, and proactively drive data product adoption
Extend existing ML libraries and frameworks
2+ years of research and/or industry experience
Solid background in applied math, computer science, statistics, or related technical field
Deep skills in two or more of: applied statistics, optimization, NLP, predictive modeling, recommender systems, ranking systems, reinforcement learning
Strong computational skills; ability to implement data science pipelines and applications at scale using a general programming language (e.g, Python, Java, Scala)
Proficient with relational databases and SQL
Strong project management and cross-functional collaboration skills
Excellent problem solving, critical thinking, analytical and interpersonal skills
Passion for Coursera’s mission
2+ years of work experience in deployment and scaling of Machine Learning and Deep Learning algorithms on AWS cloud services (Sagemaker, Lambda, Cloudwatch, etc.)
Experience with model lifecycle management, testable code and shipping code into production
Proficient with large-scale distributed databases (e.g., Spark)
Experience with online controlled experimentation
MS or above
Coursera is an Equal Employment Opportunity Employer and considers all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, age, marital status, national origin, protected veteran status, disability, or any other legally protected class.
If you are an individual with a disability and require a reasonable accommodation to complete any part of the application process, please contact us at firstname.lastname@example.org.