Associate Fraud Strategy Data Scientist
Cypress
San Jose, CA, United States
14 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Starter
Experience required
0 years minimum
Compensation
$104,000.0
Working hours
Regular working hours
Job source
Tech stack
Microsoft Excel
Amazon Web Services
Data Analysis
Big Data
Data Mining
Data Visualization
Fraud Prevention and Detection
Python (Programming Language)
Payment Gateway
SQL Databases
Tableau (Software)
Scripting
+1 more
Data Analytics
Job description
Associate Fraud Strategy Data Scientist This is an exciting opportunity to join a growing global company in the cloud-based software industry. 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:
- Design rules to detect/mitigate fraud.
- Develop Python scripts and models that support strategies.
- Investigate novel/large cases and identify root cause.
- Set strategy for different risk types.
- Work with product/engineering to improvement control capabilities and 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.
- 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
- 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, i.e. Tableau.
- 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
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