Motion Recruitment
Overview
Location:
Hybrid (Client located in Mountain View, CA). This position requires working onsite Monday-Friday. Work Schedule:
Monday through Friday (8:00 AM – 5:00 PM PST). Contract:
12+ months Role:
Fraud Data Analyst within the Trust & Safety team of a global financial technology company. Responsibilities
Analyze data to uncover patterns of fraud and gain a comprehensive understanding of how bad actors operate. Transform data into actionable insights for stakeholders. Create intuitive dashboards to monitor and mitigate fraudulent patterns. Formulate requirements for data engineering teams to ensure access to lucid, accurate, and consistent datasets. Build and maintain dashboards to assess the efficacy of controls in mitigating fraud while minimizing impact on customers. Equip policy teams with a comprehensive understanding of the ecosystem to identify opportunities for improvement. Perform in-depth exploration and analysis of internal and external data sources. Identify developing patterns of fraudulent activities across the company’s product range. Communicate regularly with leadership, peers, and stakeholders about goals and measurable business outcomes. Collaborate with local and global teams in policy, product, data engineering, data science, and R&D. Qualifications
Required Qualifications: +4 years of experience analyzing complex datasets and providing business recommendations. +4 years of experience in an e-commerce, payments, or financial services company. +4 years of experience building dashboards and data visualization. Extensive SQL experience, specifically in your current role. Proven ability to work independently and make decisions with minimal direction within assigned timelines. Able to express thoughts and ideas in fluent and concise manner. Preferred Qualifications: Background in fraud prevention, with emphasis on tax fraud. Experience building ETL pipelines. Experience with Tableau/QlikView or other data visualization software. Experience with Github / Splunk / Python. Bachelor’s degree, or foreign equivalent, in computer science, information systems management, engineering (any field), or closely related quantitative discipline. Benefits
Medical Insurance & Health Savings Account (HSA) 401(k) Applicants must be currently authorized to work in the U.S. on a full-time basis now and in the future.
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Location:
Hybrid (Client located in Mountain View, CA). This position requires working onsite Monday-Friday. Work Schedule:
Monday through Friday (8:00 AM – 5:00 PM PST). Contract:
12+ months Role:
Fraud Data Analyst within the Trust & Safety team of a global financial technology company. Responsibilities
Analyze data to uncover patterns of fraud and gain a comprehensive understanding of how bad actors operate. Transform data into actionable insights for stakeholders. Create intuitive dashboards to monitor and mitigate fraudulent patterns. Formulate requirements for data engineering teams to ensure access to lucid, accurate, and consistent datasets. Build and maintain dashboards to assess the efficacy of controls in mitigating fraud while minimizing impact on customers. Equip policy teams with a comprehensive understanding of the ecosystem to identify opportunities for improvement. Perform in-depth exploration and analysis of internal and external data sources. Identify developing patterns of fraudulent activities across the company’s product range. Communicate regularly with leadership, peers, and stakeholders about goals and measurable business outcomes. Collaborate with local and global teams in policy, product, data engineering, data science, and R&D. Qualifications
Required Qualifications: +4 years of experience analyzing complex datasets and providing business recommendations. +4 years of experience in an e-commerce, payments, or financial services company. +4 years of experience building dashboards and data visualization. Extensive SQL experience, specifically in your current role. Proven ability to work independently and make decisions with minimal direction within assigned timelines. Able to express thoughts and ideas in fluent and concise manner. Preferred Qualifications: Background in fraud prevention, with emphasis on tax fraud. Experience building ETL pipelines. Experience with Tableau/QlikView or other data visualization software. Experience with Github / Splunk / Python. Bachelor’s degree, or foreign equivalent, in computer science, information systems management, engineering (any field), or closely related quantitative discipline. Benefits
Medical Insurance & Health Savings Account (HSA) 401(k) Applicants must be currently authorized to work in the U.S. on a full-time basis now and in the future.
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