Associate Fraud Strategy Data Scientist
ANRGI TECH
Full-time
On-site
Alviso, Alviso, United States
JOB DESCRIPTION:
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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 ******. This position requires a person who has experience with performing analytics, refining risk strategies, and developing predictive algorithms preferably in the risk domain.
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Weâd love to chat if you have:
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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.
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Bachelorâs degree in Data Analytics, Data Science, Mathematics, Statistics, Data Mining or related field or equivalent practical experience
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Experience using statistics and data science to solve complex business problems
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Proficiency in SQL, Python, Excel including key data science libraries
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Proficiency in data visualization including Tableau
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Experience working with large datasets
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Ability to clearly communicate complex results to technical experts, business partners, and executives including development of dashboards and visualizations, ie Tableau.
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Comfortable with ambiguity and yet able to steer analytics projects toward clear business goals, testable hypotheses, and action\-oriented outcomes
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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.
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Desirable to have experience or aptitude solving problems related to risk using data science and analytics
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Bonus: Experience with AWS, knowledge of fraud investigations, payment rule systems, working with ML teams, fraud typologies
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Key Job Functions
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Design rules to detect\/mitigate fraud
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Develop python scripts and models that support strategies
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Investigate novel\/large cases
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Identify root cause
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Set strategy for different risk types
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Work with product\/engineering to improvement control capabilities
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Develop and present strategies and guide execution
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Expected Outcome in 6\-12 months
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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.
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Utilize data analysis to design and implement fraud strategies
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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.
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Make business recommendations to leadership and cross\-functional teams with effective presentations of findings at multiple levels of stakeholders.
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Development of dashboard and visualizations to track KPI of fraud strategies implemented
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Preferred Skills
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Data analytics and models
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Rule development
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Dashboard Creation
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Project Management
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Strong Communication
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MUST HAVE:<\/b>
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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.
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Bachelorâs degree in Data Analytics, Data Science, Mathematics, Statistics, Data Mining or related field or equivalent practical experience.
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Experience using statistics and data science to solve complex business problems.
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Experience in SQL, Python, Excel including key data science libraries.
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Experience applying statistics and data science to tackle intricate business challenges especially in Fraud mitigation.
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Experience in data visualization including Tableau.
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Experience working with large datasets.
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