Sr Data Scientist

We Impact Lives Through Purpose-Driven Work in A People First Culture

Ascend Learning, a leading healthcare and learning technology company, is the connection between a powerful portfolio of brands serving students, educators, and employers with outcomes-based, data-driven solutions across the lifecycle of learning. From testing to certification, Ascend Learning products are used by physicians, emergency medical professionals, nurses, allied health professionals, certified personal trainers, financial advisors, skilled trades professionals and insurance brokers.

Headquartered in Burlington, MA, with additional office locations and hybrid and remote workers in cities across the U.S., Ascend Learning was recognized by Newsweek and Plant-A Insights Group as one of America’s 2025 Greatest Workplaces as well as America’s Best Places to work for Mental Well-Being for 2025.

We're always looking for talented, passionate professionals to join us in our mission to help change lives. If this sounds like an environment where you'd thrive, read on to learn more.

WHAT YOU'LL DO

As a Senior Data Scientist in the Data & Business Intelligence org, you’ll be the analytical engine behind Ascend Learning’s test security function — building the models, reports, and intelligence that empower security analysts and Psychometricians across our portfolio of brands to protect the integrity of every assessment we deliver. You’ll leverage a modern data stack (Snowflake, SQL Server, Tableau) and apply statistical modeling and machine learning to surface insights that drive decisions at the highest levels of the organization, working alongside a team of seasoned data professionals who bring deep expertise across the full data lifecycle.

WHERE YOU’LL WORK

• This position will work a hybrid schedule from our Leawood, KS or Burlington, MA office preferred. Remote candidates will be considered within the United States.

HOW YOU’LL SPEND YOUR TIME

• Threat Detection & Behavioral Analysis: Design and implement statistical models, anomaly detection algorithms, and machine learning pipelines to identify suspicious test-taking patterns, proxy testing, impersonation, and item exposure across large-scale assessment datasets.

• Advanced Modeling: Build and maintain predictive and classification models — including logistic regression, clustering, random forest, and NLP-based flagging — to surface security risks and prioritize investigation queues.

• Executive Communication: Independently prepare and present findings, dashboards, and security briefings to senior leadership — translating complex analytical outputs into clear, actionable narratives.

• Incident Reporting: Author detailed analytical reports supporting security investigations, including methodology documentation, evidence summaries, and recommended actions.