This is an exciting opportunity to join a growing global company in the cloud-based software industry. This is a hybrid position. We are looking for a talented, enthusiastic and dedicated person to support the Fraud Risk Strategy team. The incumbent will be responsible for supporting key projects associated with fraud detection, risk analysis and loss mitigation. This position requires a person who has experience with performing analytics, refining risk strategies, and developing predictive algorithms, preferably in the risk domain.
Responsibilities:
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
Requirements:
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
Bachelors degree in computer science, Engineering, Mathematics, Statistics, Data Mining or related field or equivalent practical experience
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, i.e. Tableau.
Comfortable with ambiguity and yet able to steer analytics projects toward clear business goals, testable hypotheses, and action-oriented outcomes
Demonstrated analytical thinking through data-driven decisions, as well as the technical know-how, and ability to work with your team to make a big impact.
Bonus: Experience with AWS, knowledge of fraud investigations, payment rule systems, working with ML teams, fraud typologies, or credit products