Data Scientist, Test Security

Job Description

Job Description

Career Title: Data Scientist, Test Security

Department: Measurement Services 

Salary: Competitive salary commensurate with experience

FLSA: Exempt

Note: Union dues are 1.44% of bi-weekly pay 

Career Summary: 

The American Nurses Enterprise (ANE) is seeking a Data Scientist, Test Security to help safeguard the validity, integrity, and credibility of its certification programs. This role applies data forensics, advanced analytics, and investigative expertise to identify anomalies, assess security risks, and detect emerging trends. The Data Scientist manages the full data lifecycle by gathering, preparing, validating, and analyzing information from multiple systems and sources. In collaboration with cross-functional teams, this position leads initiatives that strengthen test security practices, improve operational processes, and enhance program effectiveness. The role also develops clear, meaningful reports, dashboards, and presentations that translate complex findings into actionable insights for strategic and operational decision-making.

Join the American Nurses Enterprise (ANE) and be part of the team building a healthy world through The Power of Nurses®. Our goals are to (1) Elevate the Profession of Nursing Globally 

(2) Evolve the Practice of Nursing to Improve Health, Health Care, and Health Equity and (3) Ensure the Professional Success of Nurses. Our core values: Trusted, Inclusive, Innovative and Empowered guide everything we do. We are committed to creating a supportive and dynamic workplace where employees can thrive. 

We understand the importance of work-life balance and offer flexible work arrangements and generous paid time off. Our modern office spaces are designed to foster collaboration and creativity. The collaborative culture and supportive team environment make ANE a great place to grow your career.

What You Will Do:

Data Management, Quality & Analysis

• Ensures data are accurate, reliable, and actionable to support operational and strategic initiatives.
• Collects, prepares, integrates, and validates data from multiple systems and sources.
• Monitors and maintains data quality standards, identifying and resolving inconsistencies or gaps.
• Performs exploratory and advanced analyses to identify trends, risks, opportunities, and business insights.
• Develops queries, data pipelines, and analytical processes that improve data accessibility and reliability.
• Establishes and maintains documentation related to data sources, definitions, methodologies,and processes.

Test Security Analytics & Data Forensics

• Protects the integrity of certification programs through data-driven detection and investigation of security risks.
• Analyzes examination and test taker data to identify patterns, anomalies, and indicators of potential misconduct or security threats.
• Designs and executes data forensic investigations to support test security reviews and incident response activities.
• Develops and refines statistical models, risk indicators, and monitoring methodologies to detect emerging threats.
• Partners with psychometric and test development teams to investigate suspicious testing activity and validate findings.
• Documents methodologies, findings, and recommendations to support decision-making and audit requirements.

Reporting, Visualization & Stakeholder Communication

• Transforms complex data into meaningful insights that support informed decisions across the organization.
• Develops and maintain recurring and ad hoc reports, dashboards, scorecards, and visualizations.
• Translates complex analytical findings into clear, actionable recommendations tailored to diverse audiences.
• Presents results to technical and non-technical stakeholders, including leadership and cross[1]functional teams.
• Defines and monitors key performance indicators (KPIs) related to test security, certification operations, and program effectiveness.
• Supports strategic planning and operational decision-making through data-driven insights.

Research and Special Projects

• Leads initiatives that enhance test security capabilities, operational effectiveness, and organizational performance.
• Collaborates across multiple workgroups to identify opportunities for increased efficiency, effectiveness, and risk mitigation.
• Evaluates existing processes and implements data-driven solutions that improve operational outcomes.
• Recommends and supports the adoption of new analytical tools, methodologies, and best practices.
• Maintains awareness of industry trends and advancements, including data analysis techniques and processes. Shares findings with the department and applies this knowledge to enhance ANCC operations and inform product development.

What you bring to the American Nurses Enterprise:

Education

• Master’s Degree in Psychometrics, Data Analytics, Business Analytics, Industrial[1]Organizational Psychology, or related field, or an equivalent combination of education and experience.

Related Work Experience:

• 3-5 years data analysis, business intelligence, statistical analysis, or a related analytical role managing large datasets, or related field. 
• Experience leading analytical projects from concept through implementation required. Strong reporting and data visualization skills required. Experience working in high-stakes certification, credentialing, or assessment programs preferred.

Computer skills required:

• Knowledge of statistical analysis techniques and data validation methodologies
• Experience working with large and complex datasets
• Demonstrated skill in using software packages for data analysis (e.g., R, SPSS, Winsteps)
• Fluency in using office computer software (e.g., Microsoft Word, Excel, PowerPoint)
• Experience with data visualization and reporting tools
• Knowledge of psychometric, assessment, testing, or exam administration data (preferred)

Other skills required:

• Strong analytical and problem-solving skills
• Attention to detail and commitment to data accuracy 
• Ability to identify meaningful trends, patterns, and anomalies within large datasets 
• Strong written and verbal communication skills 
• Ability to present findings to both technical and non-technical audiences