Job Title: Associate Fraud Strategy Data Scientist

Location: San Jose, CA 95002

Duration: 12 Months

Job Type: Contract

Work Type: Hybrid

Pay rate - $53-53 per/ hr.

Job Description:

• 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 at Client.
• This position requires a person who has experience with performing analytics, refining risk strategies, and developing predictive algorithms preferably in the risk domain.

We’d love to chat if you have:

• 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.
• Bachelor’s degree in Data Analytics, Data Science, 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, ie 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.
• Desirable to have experience or aptitude solving problems related to risk using data science and analytics
• Bonus: Experience with AWS, knowledge of fraud investigations, payment rule systems, working with ML teams, fraud typologies

Key Job Functions:

• 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

Expected Outcome in 6-12 months:

• 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

Preferred Skills:

• Data analytics and models
• Rule development
• Dashboard Creation
• Project Management
• Strong Communication