Data Scientist II, Machine Learning
United States (Remote)
Coursera
Learn new job skills in online courses from industry leaders like Google, IBM, & Meta. Advance your career with top degrees from Michigan, Penn, Imperial & more.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 and collaborative Machine Learning Data Scientist with strong experience in cloud services. In this role, you will own Coursera’s content forecasting engine, power our ability to identify content and skills gaps, and help scale our ML systems. Our ideal candidate possesses a strong statistical and computational skillset, is collaborative and impact-driven, and shares our passion for education.
Your responsibilities:
- Ideate, prototype, and productionize ML solutions to improve Coursera’s content forecasting engine, perform learner and content segmentation, and identify content and skills gaps.
- Design, deploy and scale end-to-end machine learning / deep learning pipelines and models with AWS cloud services
- Extend existing ML libraries and frameworks
- Partner with Product Managers and Engineers to identify and articulate opportunities, build efficient and scalable ML solutions, and proactively drive data product adoption
- Distill insights from complex data and/or data product results; communicate findings clearly to both technical and non-technical audiences
- Develop metrics to evaluate data product performance and drive improvements
Basic Qualifications:
- 2+ years of work experience in deployment and scaling of Machine Learning and Deep Learning algorithms on AWS cloud services (Sagemaker, Lambda, Cloudwatch, etc.)
- 2+ years of experience with one or more of the following: forecasting models, natural language processing, ranking systems, or similar
- Solid background in machine learning frameworks like TensorFlow, PyTorch, Scikit Learn, etc.
- Knowledge of software development tools like Git, CI/CD, Docker, etc.
- Experience with one or more programming languages (e.g., Python, R) and proficient with relational databases and SQL
- Masters degree or above
- 3+ years of research and/or industry experience
- Strong project management and cross-functional collaboration skills
- Excellent problem solving, critical thinking, analytical and interpersonal skills
If this opportunity interests you, you might like these courses on Coursera:
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 accommodations@coursera.org.
Please review our CCPA Applicant Notice here.
Tags: AWS BERT Causal inference CI/CD Computer Science Deep Learning Docker Git Lambda Machine Learning NLP Pipelines Python PyTorch R RDBMS Research SageMaker Scikit-learn SQL TensorFlow
Perks/benefits: Career development
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