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P
Pearson
Lead Specialist, Data Scientist
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Based on Minnesota data
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What they do
A Data Scientist utilizes skills and experience to systematically answer questions using data to provide actionable recommendations. Commonly utilizes advanced statistical analysis and machine learning techniques. Common responsibilities also include data cleaning and data management.
$104,749 / year median in Minnesota
+16% projected growth
Job Description
Lead Specialist, Data Scientist Position Summary 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. Key Responsibilities Advanced Data Forensics & Fraud Detection 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. Investigative Analytics 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. Machine Learning & Predictive Modeling 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. Intelligence & Threat Analysis 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. Reporting & Visualization 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. Required Qualifications 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.