Full-Time

Senior Data Scientist

Updated on 7/21/2026

College Board

College Board

Compensation Overview

$153k - $166k/yr

Remote in USA

Remote

Fully remote within the United States; hybrid option available for candidates near CB offices (Tuesdays and Wednesdays in office).

Category
Data & Analytics (1)
Required Skills
Microsoft Azure
Agile
Python
NoSQL
Neural Networks
SQL
Machine Learning
Microservices
AWS
Pandas
REST APIs
DevOps
Serverless
Google Cloud Platform
Requirements
  • Master’s in a quantitative discipline or computer science, OR a Bachelor’s and 10+ years related experience
  • Programming expertise in Python and pandas, advanced skills in SQL
  • Expertise in data and statistical analysis
  • Proven experience in developing Machine Learning (ML) and Deep Learning (DL) solutions to solve real-world problems
  • Experience with SQL and NoSQL databases
  • A passion for solving difficult problems creatively
  • Excellent communication and listening skills, and are able to help others understand both problems and solutions
  • The ability to tell a story with your data
  • Worked within a close knit team and enjoy helping your colleagues succeed
  • Knowledge in CI/CD, DevOps and Agile
  • Knowledge in developing applications on a Serverless or Microservices cloud platform (AWS/Azure/GCP, etc.)
Responsibilities
  • 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
  • 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, documented analyses and models that lend themselves to automation
  • Help the team break down the work into manageable tasks and support our Agile maturity
  • Substantially improve the team’s productivity and quality by enhancing tools, processes, and code structure
  • Advise other teams on Machine Learning projects and assist with establishing Machine Learning governance
  • Assist in the identification and resolution of production issues

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