Associate Fraud Strategy Data Scientist

Day to day:
• Design rules to detect/mitigate fraud
• Develop python scripts and models that support strategies
• Investigate novel/large cases
• Identify root cause
• Set strategy for different risk types
• Work with product/engineering to improvement control capabilities
• Develop and present strategies and guide execution
• Work closely with team members and stakeholders to consult, design, develop, and manage fraud strategies and rules that not only solve emerging fraud trends but also provide a great experience to end customers.
• Utilize data analysis to design and implement fraud strategies
• Collaborate with cross-functional stakeholders including product managers and engineering teams to deploy data-driven fraud solutions that operate at scale and in real time for end customers.
• Make business recommendations to leadership and cross-functional teams with effective presentations of findings at multiple levels of stakeholders.
• Development of dashboard and visualizations to track KPI of fraud strategies implemented

Must Haves:
• Maximum 2 years of experience in risk analytics, data analysis, and data science within relevant industry experience in eCommerce, online payments, user trust/risk/fraud, or investigation/product abuse.
• Experience using statistics and data science to solve complex business problems
• Proficiency in SQL, Python, Excel including key data science libraries
• Proficiency in data visualization including Tableau
• Experience working with large datasets
• Ability to clearly communicate complex results to technical experts, business partners, and executives including development of dashboards and visualizations, ie Tableau.
• Bachelor’s degree in Data Analytics, Data Science, Mathematics, Statistics, Data Mining or related field or equivalent practical experience

Pluses:
• Experience with AWS, knowledge of fraud investigations, payment rule systems, working with ML teams, fraud typologies