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Pearson Apprentice, Analytics Engineer in California

Apprentice, Analytics Engineer - ( 2110128 )

Description

We are the world’s learning company with more than 24,000 employees operating in 70 countries. We combine world-class educational content and assessment, powered by services and technology, to enable more effective teaching and personalized learning at scale. We believe that wherever learning flourishes so do people.

At Pearson, we’re committed to a world that’s always learning and to our talented team who make it all possible. By embracing a massive digital transformation that includes highly experiential and personalized learning, we are always re-examining and continuously improving the way people learn best, whether it’s one child in our own backyard or an education community across the globe. We are bold thinkers and standout innovators who are mission-driven and motivate each other to explore new frontiers in an environment that supports and inspires us to always be better.

We are looking for a hands-on, highly motivated and capable Analytics Engineer Apprentice to work in our Global Product Technology (GPT) organization to support teams working existing and next generation learning platforms. The Apprentice will work with a multi-disciplinary team of engineers, data scientists and operational leads to provide strategic information on all areas of GPT’s technology operations, product services and system reliability as well as providing insights used to monitor and track GPT’s engineering goals. Pearson is an Equal Opportunity and Affirmative Action Employer and a member of E-Verify. All qualified applicants, including minorities, women, protected veterans, and individuals with disabilities are encouraged to apply.

Qualifications

Responsibilities:

  • Build relationships with GPT operational leadership to understand and prioritize operational reporting and analysis needs

  • Work with GPT engineering teams to extract data, build analysis frameworks, establish OKRs & metrics that deliver insights on GPT’s operational efficiency and system reliability

  • Partner with GPT engineering teams to implement QoS telemetry and measurement instrumentation to understand the operational performance of Pearson products

  • Identify and execute process improvements and assist with automation projects for reporting and analytics

  • Develop reports and visualizations for internal department use detailing operational performance of GPT products and services

  • Influencing technology teams through presentation of data-based recommendations that communicate the state of operational excellence and efficiency of GPT product engineering teams

Qualifications:

  • The ideal candidate will be detail oriented, self-directed, self-motivated, with a strong capacity for working successfully and flexibly with members across the organization.

  • BSc or higher in computer science, statistics, mathematics, physical science, engineering, or a comparable related technical field.

  • Currently participating in NC State University AI Academy Program.

Preferred:

  • Experience with quantitative analysis within a large-scale technology company with experience working with AWS financials and pricing and AWS operational and business intelligence data

  • Experience working with technologies and analytical platforms in AWS environments such as New Relic, Snowflake, Databricks using tools such as Tableau and SQL

  • Experience manipulating data using statistical analysis techniques such as time-series analysis, multiple linear/logistic regression, anomaly detection, forecasting and simulation

Note that that the role duration is Aug 2, 2021 - July 4, 2022.

Primary Location : US-NC-Durham

Other Locations : US-California

Work Locations :

US-NC-Durham-5425 Page Churchill

5425 Page Road

Durham27703

Job : Project/Temporary Workforce

Organization : Technology & Operations

Employee Status : Fixed Term

Job Type : Apprenticeship

Job Level : Entry Level

Shift : Day Job

Travel : No

Job Posting : Jul 15, 2021

Job Unposting : Ongoing

Schedule: : Part-time Temporary

Req ID: 2110128

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