Data Scientist, Data Science Team - College Board

Senior Data Scientist, Data Science Team

College Board – Technology Division

Location: This is a fully remote role. Candidates who live near CB offices have the option of being fully remote or hybrid (Tuesday and Wednesday in office).

Type: This is a full-time position

About the Team

The Data Science team provides critical insights and tools to help the executive leadership team, technology teams, and business units optimize test delivery, test development, and test security. Our expertise is understanding a wide array of business problems and using a variety of techniques including data analysis, machine learning, and software engineering to create value from data and support decision making. We have a passion for data analysis, programming, applying new technologies, and building practical solutions. Our tight-knit, self-organized team of Data Scientists and Machine Learning Engineers collaborates closely and uses creative problem solving to tackle difficult challenges for many of the organization’s strategic initiatives. We love having virtual happy hours and celebrating our accomplishments.

About the Opportunity

As a Senior Data Scientist, you are a passionate collaborator who works closely with team members and stakeholders. You relish the opportunity to bring your ideas, love of coding, data savvy, and business acumen to improve processes that are expensive or impossible to perform without machine learning. You are not shy about taking on new work you may not have done before while eagerly building machine learning models to support the new digital testing platform or eagerly providing executive leadership critical insights to make strategic decisions.

In this role, you will

Develop machine learning applications (40%)

• Design and implement high quality software using the latest and greatest cloud and machine learning technologies
• Independently manage and complete all the work needed to deliver small or medium sized applications and analyses on time and at a very high level of quality
• Help identify and build major components of complex machine learning models
• Judiciously evaluate the effectiveness and fairness of models and articulate considerations and concerns around implementing models in the context of the business application
• Build functions, APIs, and data stores to make predictions and analyses accessible to other systems

Data engineering, exploration, and analysis (40%)

• Design and maintain scalable data pipelines that transform operational data into reliable, production-ready datasets
• Create insights from existing data and drive the collection of new data
• Communicate methodology and results of advanced analyses using accessible language and intuitive data visualizations
• Create reproducible,