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Staff Technical Data Analyst

Location Arcadia, United States
Posted 17-November-2018
Overview The Global Risk Strategy and Policy is looking for a Staff Technical Data Analyst to join the Business Rules Team. The position is responsible for the execution of Fraud, Credit, and Compliance strategies within our money movement ecosystem. You will apply data mining techniques to optimize rules from both statistical and business perspectives. The ideal candidate will have strong hands-on analytics, programming experience, and an understanding of risk within the broader money movement space.
Responsibilities Collaborates with business stakeholders in acting on complex, multi-source data to explore, generate and test business assumptionsJointly develops and prioritizes hypotheses that are central to address the business challenges and links them to complex, multi-source data in order to explore, generate and test business assumptionsCollaborates with others in building innovative data capture and batch/real time analytic, reporting and execution capabilities needed by the businessCollaborates with Data Architects/Product Development on changes associated with data systems or system interfaces (eg. Business Rule Engines)Recommends/sets data standards to improve quality of data and speed to analytics, reporting and executionDevelops data structures, pipelines, and/or data visualizations for rule analytics, reporting and executionCreates complex software programs and applications for acquisition, processing, and management of massive quantities of data using high-level programming languagesEnable timely reporting, analytics and execution of rulesBuild and maintain pipelines and dashboards/reports used to drive decisions across the Quickbooks Payments/PayrollProper documentation of projectsBe able to prepare audit documentationBuild and develop rules using the different languages such as Blaze code and JavaSupport rules in Zoot, using the AI tool to make changes and push to productionAnalyze existing rules to improve performance and reduce false positives Qualifications Technical experience including SQL, some form of coding (Python, Scala, etc), and ETL/scheduling such tools as Zoot, Drools and BlazeExperience in preparing data sets and reports in support of more complex analysisExperience with hypothesis testing and analyticsExperience with business/strategy analytics and reportingEntrepreneurial spirit and passionate about dataUndergrad Degree in Quantitative Field (Masters preferred) Options Apply for this job onlineApplyShareEmail this job to a friendRefer
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