Pearson has one defining goal: to help people progress in their lives through learning. We champion innovation and we invest in models for education that deliver on our promise for effective, accessible, and personal learning from early literacy, college and career readiness to professional education, through data informed instruction and inventive applications for mobile and digital learning.
Pearson, the world's leading learning company, has global-reach and market leading businesses in education, business, and consumer publishing and is listed on the London and New York stock exchanges (UK: PSON; NYSE: PSO). For more information, visit www.pearson.com.
The Personalized Learning and Analytics team (PLA) in Pearson is responsible for software development of analytics and machine learning platforms. PLA is growing and we are looking for a new team member to build a machine learning solution for Pearson s Global Learning Platform (GLP). Together with a highly multi-disciplinary team of engineers, data scientists, strategic partners, product managers and subject domain experts you will work on building adaptive solutions powered by big data. You will work on a best-in-class cloud computing platform, with cutting edge big data tools at your disposal while having access to experts in education, engineering and data science.
Pearson is an Equal Opportunity and Affirmative Action Employer, and a member of E-Verify. All qualified applicants, including minorities, women, veterans, and people with disabilities are encouraged to apply.
- Developing scalable data processing pipelines for analytical and predictive platform services
- Collaborate with other data scientists and engineers to find effective solutions to technical challenges
- Provide recommendations, guidance and options to support Pearson s GLP product development road map
- Work closely with engineers to build, test, deploy and troubleshoot machine learning / algorithm based software
- MSc or higher in computer science, statistics, mathematics, physical science, engineering, or a comparable related technical field
- 5+ years of industry experience in engineering, data science or related areas
- Demonstrated mastery in communication of technical ideas to non-technical audiences
- Ability to translate customer goals into practical engineering solutions
- Good understanding of foundational statistics concepts and algorithms: linear/logistic regression, random forest, boosting, NNs, etc.
- Strong programming skills with fluency in at least one of Python or R, Java, Scala, C/C++
- Ability to access, manage, transfer, integrate and analyze complex datasets, especially using SQL or map-reduce techniques
- Familiarity with libraries such as Spark ML, Tensor flow, scikit-learn, MLib, DLib, Pandas or others like H2O, Databricks
- Familiar with industry standard software engineering practices using CI/CD tools and infrastructure with a working knowledge of Unix/Linux systems
- Experience with working on large data sets, especially with Hadoop and Spark
- Experience with cloud computing platforms such as AWS
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