Job Title: Data Scientist – Risk & Fraud Analytics Location: Onsite – Atlanta, GA Duration: 12 Months (Contract) Job Description: We are seeking a highly analytical and detail-oriented Data Scientist with a strong background in fraud and risk analytics. This role will involve analyzing complex datasets, developing predictive models, and deriving actionable insights to detect risky behavior and prevent fraudulent activities across various systems and services. The ideal candidate will have extensive experience in machine learning, fraud detection, and working with large datasets in cloud environments. Key Responsibilities: • Collect, clean, and analyze large and complex datasets from multiple sources. • Develop and deploy machine learning models to detect, predict, and prevent fraudulent transactions. • Apply statistical methods and AI/ML techniques to create data-driven solutions. • Conduct deep-dive investigations into fraud trends and create detailed reports. • Collaborate with fraud operations, compliance, and engineering teams to implement real-time fraud detection systems. • Define and monitor key performance indicators (KPIs) for model performance. • Stay up to date with emerging fraud tactics and industry best practices. Required Qualifications: • Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Economics, or a related field. • 10+ years of professional experience in data science. • Proficiency in Python, SQL, and SAS. • Strong understanding of supervised and unsupervised fraud detection techniques (e.g., anomaly detection, behavioral modeling, network analysis). • Experience working with large datasets and cloud platforms such as AWS, GCP, or Azure. • Strong analytical skills to identify trends and root causes. • Experience with AI design and responsible AI use. • Expertise in data visualization using tools like Power BI or Tableau. Preferred Skills: • Familiarity with graph analytics or network-based fraud detection tools. • Knowledge of regulatory frameworks and compliance related to fraud and financial crime. • Excellent communication skills and ability to translate complex technical findings to non-technical stakeholders.