ESRhealthcare
Associate Fraud Strategy Data Scientist San Jose, CA
ESRhealthcare, San Jose, California, United States, 95199
Overview
Associate Fraud Strategy Data Scientist, San Jose, CA. Hybrid position; candidates must be based in the San Jose area. Role focuses on fraud detection, risk analysis, and loss mitigation within the Fraud Risk Strategy team at Bill.com. The ideal candidate has analytics experience, refines risk strategies, and develops predictive algorithms in the risk domain. Responsibilities
Design rules to detect and mitigate fraud. Develop Python scripts and models to support fraud strategies. Investigate novel/large cases and identify root causes. Set strategy for different risk types and work with product/engineering to improve control capabilities. Develop and present strategies and guide execution; collaborate with cross-functional stakeholders to deploy data-driven fraud solutions at scale and in real time. Monitor and manage fraud KPIs with dashboards and visualizations. Provide business recommendations to leadership and cross-functional teams with effective presentations. Qualifications
Bachelor’s degree in Data Analytics, Data Science, Mathematics, Statistics, Data Mining or related field or equivalent practical experience. 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. 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 (e.g., Tableau). Comfortable with ambiguity and able to steer analytics projects toward clear business goals, testable hypotheses, and action-oriented outcomes. Preferred Skills
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. Notes
Contract role serving multiple leaves over a 1-year period; potential to extend based on business need and performance. Day shift: Monday–Friday, Pacific Time. Multiple Zoom interviews (2–3) with a SQL assessment during the first interview.
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Associate Fraud Strategy Data Scientist, San Jose, CA. Hybrid position; candidates must be based in the San Jose area. Role focuses on fraud detection, risk analysis, and loss mitigation within the Fraud Risk Strategy team at Bill.com. The ideal candidate has analytics experience, refines risk strategies, and develops predictive algorithms in the risk domain. Responsibilities
Design rules to detect and mitigate fraud. Develop Python scripts and models to support fraud strategies. Investigate novel/large cases and identify root causes. Set strategy for different risk types and work with product/engineering to improve control capabilities. Develop and present strategies and guide execution; collaborate with cross-functional stakeholders to deploy data-driven fraud solutions at scale and in real time. Monitor and manage fraud KPIs with dashboards and visualizations. Provide business recommendations to leadership and cross-functional teams with effective presentations. Qualifications
Bachelor’s degree in Data Analytics, Data Science, Mathematics, Statistics, Data Mining or related field or equivalent practical experience. 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. 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 (e.g., Tableau). Comfortable with ambiguity and able to steer analytics projects toward clear business goals, testable hypotheses, and action-oriented outcomes. Preferred Skills
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. Notes
Contract role serving multiple leaves over a 1-year period; potential to extend based on business need and performance. Day shift: Monday–Friday, Pacific Time. Multiple Zoom interviews (2–3) with a SQL assessment during the first interview.
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