Data Scientist, Fraud Analytics & Technical Writing (3951)

GBG•Atlanta, GA

About The Position

Join GBG’s Go‑to‑Market Data Science & Analytics team, a newly established, high‑impact function shaping how we demonstrate value to customers and empower internal teams with actionable insights. As a Data Scientist – Fraud Analytics & Technical Writing, you’ll analyze large, complex datasets to surface fraud patterns, translate findings into clear business narratives, and create high‑quality technical documentation that standardizes methods and accelerates adoption across the organization. You’ll partner cross‑functionally with Sales, Product, and Operations, design dashboards that communicate trends, and influence roadmap and strategy—while building scalable, automated processes that elevate decision‑making and customer outcomes

Requirements

2+ years of hands-on experience in data analytics, with demonstrated success in customer-facing teams or process automation roles
Excellent technical writing and communication skills
Strong proficiency in Python/R, SQL, and 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
Master’s degree in Data Science or related field preferred; PhD a plus
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

Nice To Haves

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

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