Data Scientist, Fraud Analytics & Technical Writing

About This Role

Join GBG's Go-to-Market Data Science & Analytics team to analyze complex datasets, identify fraud patterns, translate findings into clear business narratives, and create high-quality technical documentation.

Responsibilities

• Analyze large, complex datasets to detect patterns, anomalies, and emerging fraud trends
• Collaborate with internal teams to validate findings and refine detection strategies
• Translate key findings into clear, compelling insights that demonstrate solution value to prospective customers
• Support the development of standardized frameworks to quantify business impact across customer profiles
• Create and maintain high-quality technical documentation, including methodologies, workflows, and system processes
• Translate complex analytical findings into clear, actionable insights for both technical and non-technical audiences
• Ensure documentation is standardized, accurate, and easily accessible for internal teams
• Work closely with cross-functional teams to implement data-driven solutions
• Design dashboards and reports to communicate fraud trends and detection results effectively
• Provide regular updates and recommendations to stakeholders based on data-driven findings

Requirements

• 2+ years of hands-on experience in data analytics
• Excellent technical writing and communication skills
• Strong proficiency in Python/R
• Strong proficiency in SQL
• Experience with statistical analysis libraries (pandas, scikit-learn, etc.)
• Experience with data visualization tools (Quicksight, Tableau, Power BI, or similar)
• Familiarity with cloud platforms (AWS, Azure, or GCP) and modern data stack tools

Qualifications

• Master's degree in Data Science or related field preferred; PhD a plus
• 2+ years of hands-on experience in data analytics, with demonstrated success in customer-facing teams or process automation roles

Nice to Have

• Domain expertise in identity verification, fraud detection, and/or financial services
• Experience presenting technical findings to prospects or clients during sales processes
• Knowledge of predictive modeling and machine learning
• Experience analyzing customer data and translating technical findings into compelling business narratives
• Knowledge of statistics and ROI calculation frameworks
• Ability to create presentations that communicate value propositions to both technical and business stakeholders
• Familiarity with cross-functional collaboration processes

Skills

* Required skills