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Machine Learning Engineer
Pearson
Centennial, CO, United States
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Description
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.
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.
Job Description:
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. Together with a highly multi-disciplinary team of engineers, scientists, strategic partners, product managers and subject domain experts you will work on building 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.
• - Develop scalable data processing pipelines
• - Collaborate with other engineers, and scientists to find effective solutions to technical challenges
• - Provide input for product road-maps
• - Work closely with engineers to build, test, deploy and troubleshoot machine learning/ algorithm based software
Qualifications
• MSc or higher in computer science, statistics, or comparable statistically driven science field
• Good understanding of foundational statistics concepts and algorithms: linear/logistic regression, random forest, boosting, ANN’s, etc.
• Passion for learning (new problem domains, algorithms, tools etc) and for analyzing data
• Fluency in at least one of Python, Java, Scala, C/C++
• Working knowledge of Unix/Linux systems
• Ability to access, manage, transfer, integrate and analyze complex datasets, especially using SQL
• Familiarity with libraries such as Spark ML, Tensor flow, scikit-learn (or others like H2O, Databricks)
Preferred Qualifications
• 2+ years of industry experience in engineering, data science or related areas
• Experience with working on large data sets, especially with Hadoop and Spark
• Experience with distributed databases such as MongoDB, HBase, Cassandra etc
• Experience with cloud computing platforms such as AWS
• Experience with data visualization tools such as Tableau, D3.js