Data Scientist

Data Scientist

Rate : ALAP
Location Atlanta
Last Date : 7/25/2025
Hybrid

Key Responsibilities

Collect, clean, and analyze large, complex datasets from multiple sources.
Develop predictive models and machine learning algorithms to support decision-making and improve business performance.
Translate business problems into data-driven solutions with measurable impact.
Develop and deploy machine learning models to detect, predict, and prevent fraudulent transactions and behavior patterns.
Analyze large volumes of structured and unstructured data from multiple sources to identify fraud trends and root causes.
Collaborate with fraud operations, engineering, and compliance teams to implement real-time fraud detection solutions.
Design and monitor KPIs to evaluate model performance and improve fraud detection systems over time.
Conduct deep-dive investigations into fraud cases, creating detailed reports and actionable insights.
Stay current with emerging fraud techniques, industry best practices, and data science tools.

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
Proficient in Python, SQL, SAS and machine learning techniques
Experience in responsible use of AI if used in solution design
Strong analytical skills and the ability to identify patterns and trends from data
Experience working with large datasets and cloud platforms (e.g., AWS, Google Cloud Platform, Azure).
Strong understanding of supervised and unsupervised fraud detection techniques, including anomaly detection, behavioral modeling, and network analysis.
Experience with visualization tools like Tableau and Power BI.

Familiarity with graph analytics or network-based fraud detection tools. Highly desired
Knowledge of regulatory frameworks and compliance issues related to fraud and financial crime. Highly desired
Strong communication skills with the ability to explain technical solutions to non-technical stakeholders. Highly desired
Bachelor s or Master s degree in Data Science, Computer Science, Statistics, Mathematics, Economics or a related field. Required
Professional experience in data science. Required 10 Years
Proficient in Python, SQL, SAS and machine learning techniques. Required 5 Years
Experience working with large datasets and cloud platforms (e.g., AWS, Google Cloud Platform, Azure). Required 5 Years
Understanding of supervised and unsupervised fraud detection techniques, including anomaly detection, behavioral modeling, and network analysis. Required
Experience with visualization tools like Tableau and Power BI. Required 5 Years
Experience in responsible use of AI if used in solution design. Required 5 Years
Strong analytical skills and the ability to identify patterns and trends from data. Required