Title : Associate Fraud Risk Data Scientist
Location : San Jose, CA
Duration : 12 Months.
JOB DESCRIPTION :
We are looking for a talented, enthusiastic and dedicated person to support the Fraud Risk Data Science Team within the Risk Data & AI Innovation Org. 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 machine learning, model development with cutting edge AI / ML frameworks, performing analytics, statistical analysis and model monitoring. Experience with LLMs and other AI tools would be a big plus.
We'd love to chat if you have :
- 2-6 years of experience in machine learning / AI, data science, risk analytics & data analysis within relevant industry experience in eCommerce, online payments, user trust / risk / fraud, or investigation / product abuse.
- Bachelor's / Master's degree in Data Science, Data Analytics, Mathematics, Statistics, Data Mining or related field or equivalent practical experience
- Experience using statistics and data science (machine learning & AI) to solve complex business problems
- Proficiency in SQL, Python, AWS, 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.
- Comfortable with ambiguity and yet able to steer AI and machine learning 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.
- Desirable to have experience or aptitude solving problems related to risk using data science and analytics
- Bonus : Experience with development and implementation of AI tools (e.g. LLMs) for risk use cases.
Key Job Functions :
Design and develop machine learning and AI models detect / mitigate fraudSupport stakeholders and cross-functional teams in effective usage of modelsDrive AI transformation for all risk management activitiesWork with product / engineering to implement, monitor and refine AI solutions and modelsExpected Outcomes :
Work closely with team members and stakeholders to consult, design, develop, and manage fraud models and AI solutions.Utilize data analysis to design and implement fraud modelsCollaborate with cross-functional stakeholders including product managers and engineering teams to deploy data-driven fraud models and AI 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 models implementedPreferred Skills :
Machine Learning & Artificial IntelligenceData ScienceModel developmentDashboard CreationProject ManagementStrong Communication Skills.