DSI is looking to analyze large and/or complex datasets, develop predictive models, and derive actionable insights to drive key business decisions and prevent fraudulent activities across products and services.
Requirements
- Proficient in Python, SQL, SAS and machine learning techniques
- Experience working with large datasets and cloud platforms (e.g., AWS, GCP, 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.
- Experience in responsible use of AI if used in solution design
- Strong analytical skills and the ability to identify patterns and trends from data
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.
Other
- 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.
- Strong analytical skills and the ability to identify patterns and trends from data
- Must be committed to the principles of equal employment and diversity, equity, and inclusion
