Data Scientist, Fraud Detection

• Design models and strategies to quickly detect transactional anomalies


• Explore, analyze and synthesize information to understand the characteristics of active fraud schemes


• Develop strategies for detecting transactional fraud


• Test the theoretical performance of fraud mitigation models, rules and tools


• Deploy fraud mitigation models, rules and tools into production


• Continuously monitor fraud patterns and model and strategy performance


• Research and develop predictive variables to improve fraud detection


• Develop, update and produce dashboards, data visualizations and reports


• Optimize and automate key fraud detection analytics processes


• Provide ad hoc advice on projects to improve fraud risk management tools


• Advise risk management teams and business sectors in the field


• Monitor industry trends to develop and update organizational best practices

Requirements

• Bachelor's degree in a related field


• A minimum of four years of relevant experience


• Other combinations of qualifications and relevant experience may be considered


• Experience in analytics with transactional data


• Experience working with cloud platforms such as IBM Cloud Pak® for Data or Microsoft Azure


• Experience with Apache Spark (via PySpark), Shiny, RStudio and Databricks


• Knowledge of French is required


• Proficiency in Python or R programming


• Proficiency in data science libraries and their limitations, including scikit-learn, pandas, Matplotlib, NumPy and SciPy


• Proficiency in SQL programming


• Knowledge of GitHub

Core Competencies

Demonstrates expertise in developing and deploying fraud detection models and strategies, utilizing advanced analytics and cloud platforms. Proficient in programming languages and data science libraries to optimize fraud detection processes and provide actionable insights.

Highest-signal resume keywords

• Fraud Detection Strategies


• Python Programming


• SQL Programming


• Apache Spark (PySpark)


• Data Visualization

ATS Optimization Keywords

Hard Skills

• Fraud Detection Analytics


• Data Analysis


• Predictive Modeling


• Cloud Platforms


• Data Science Libraries

Soft Skills

• Advisory Skills


• Collaboration

Industry Keywords

• Transactional Data


• Fraud Risk Management


• Data Visualization


• Fraud Mitigation


• Industry Trends

Tools & Technologies

• IBM Cloud Pak® for Data


• Microsoft Azure


• RStudio


• Databricks


• GitHub