The employer is deeply committed to improving student success and college graduation rates worldwide by crafting digital experiences that build community and increase student engagement. They work with over 300 higher education institutions globally, helping them better engage their students, improve the student life experience on their campuses, and ensure that they ultimately provide success for their students.
Understanding students and institutions and their behaviours through data lie at the foundation of our work to improve student success. Every data point in our systems is important to helping us achieve that goal, so we're looking for people with a strong background in data engineering and analytics to help us design, build, scale, and maintain our data pipelines and models.
As a Data Science Engineer, you will be working with various internal teams across engineering, product, and business to help solve their data needs. Your work will directly and tangibly impact the success of millions of students across the world.
In terms of the role and responsibilities, you will:
Identify the data needs of our engineering, product, and business teams, understand their specific requirements for metrics and analysis, then build efficient, scalable, accurate, and complete data pipelines to enable data-informed decisions across the company
Architect data pipelines and models that power internal analytics for our teams, as well as customer-facing data visualization product features
Drive the collection of new data and the evolution of existing data sources, collaborate with the engineering teams to manage our product instrumentation strategies and data structures
Help the product, and engineering teams understand and generalize statistical models from our research efforts, and help build data systems that would allow these models to be used directly in our product to drive student success
Work with the Product Manager on the squad to ensure productive, fast-moving sprints that deliver the maximum value to our customers
Work with the other senior engineers and architects to ensure that our integrations stack is reliable, flexible, and scalable
Help to improve the team processes of our engineering team continuously
Have at least 4 years of experience in a Data Engineering or Data Science role, with a focus on instrumenting data collection, building data pipelines and conducting data-intensive analysis
Have a strong engineering background and are interested in data
Care deeply about the integrity of data, have a good nose for inconsistencies in data, and be able to pinpoint the issue to ensure that the team is not making decisions based on inaccurate or incomplete data
Have extensive experience in a scientific computing language (e.g. Python) and SQL
Have experience building systems that process data across multiple data stores and technologies, including MySQL, Redis, Elasticsearch
Know the best practices of how different types of data should be visualized in different contexts
Have good writing and verbal communication skills
Nice to haves:
Experience working with Python web applications
Experience working in the higher-ed technology space, particularly in a Data Engineering related role
Experience working with a remote or distributed team
This is a fully remote, full-time permanent position. The Data Science Engineer must be available to work regular business hours in the Eastern time zone.