Forensic Behavioral Science Jobs in Minnesota (NOW HIRING)

Pearson Professional Assessments is seeking an experienced Data Scientist to help advance our data forensics, fraud detection, and exam security analytics capabilities. This role will focus on identifying emerging threats, developing predictive models, and generating actionable intelligence that protects the integrity of high-stakes testing programs worldwide.

The ideal candidate is passionate about solving complex analytical challenges, leveraging machine learning techniques, and transforming large datasets into meaningful insights that drive operational and security outcomes.

• Develop statistical and machine learning models to identify suspicious testing behavior, fraud patterns, and emerging threats.
• Create and maintain risk scoring methodologies that support investigative prioritization.
• Analyze candidate, test center, proctoring, identity verification, and operational datasets to identify anomalies and indicators of compromise.
• Perform exploratory data analysis to uncover hidden trends and relationships.

• Support complex investigations involving exam misconduct, proxy testing, collusion, content theft, account compromise, and other security concerns.
• Develop repeatable analytical methodologies that improve investigative effectiveness and consistency.
• Identify behavioral patterns and indicators associated with fraudulent activity.

• Design, develop, validate, and deploy predictive and anomaly detection models.
• Continuously monitor and improve model performance.
• Utilize supervised and unsupervised learning techniques to detect previously unknown threats.
• Partner with technical teams to operationalize analytical solutions.

• Collaborate with security, integrity, and operational teams to identify emerging risk trends.
• Research new fraud tactics and evolving threat vectors.
• Translate analytical findings into actionable intelligence and business recommendations.

• Develop dashboards, visualizations, and executive reporting to communicate insights.
• Present analytical findings to technical and non-technical stakeholders.
• Support strategic decision-making through data-driven recommendations.

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related field.
• 3+ years of experience in data science, fraud analytics, security analytics, risk analytics, or a related discipline.
• Strong proficiency with:
  • Python
  • SQL
  • Statistical Analysis
  • Machine Learning
  • Databricks or similar analytics platforms
• Experience working with large, complex datasets.
• Strong problem-solving and analytical skills.
• Ability to communicate complex findings to diverse audiences.

• Master's degree in a quantitative discipline.
• Experience in fraud detection, cybersecurity, investigations, digital identity, or risk management.
• Experience with:
  • XGBoost
  • Scikit-Learn
  • Spark
  • Azure Data Services
  • Splunk
  • Graph Analytics
• Knowledge of anomaly detection methodologies.
• Experience supporting investigative or intelligence functions.

• Deliver measurable improvements in fraud detection capabilities.
• Develop scalable analytical models that increase investigative efficiency.
• Identify emerging threats before they become widespread operational risks.
• Enable data-driven decision-making across security and integrity teams.
• Support the continued evolution of Pearson's advanced data forensics capabilities.

Compensation at Pearson is influenced by a wide array of factors including but not limited to skill set, level of experience, and specific location. As required by the California, Colorado, Hawaii, Illinois, Maryland, Minnesota, New Jersey, New York State, New York City, Vermont, Washington State, and Washington DC laws, the pay range for this position is as follows:    

The minimum full-time salary range is between $165,000 - $205,000.  

This position is eligible to participate in an annual incentive program, and information on benefits offered is here.  

Applications will be accepted through 24th July. This window may be extended depending on business needs