Business Intelligence Engineer II
Job Summary
BIE L5 should use statistical analysis to address VITAs biggest problems in proactively identifying defects. The candidate will have opportunities to (and will be asked to) get exposure to the modern cloud-based data technologies. The individual must be proactive in taking ownership of data ingestion from variety of source systems build data pipelines and analytics have excellent problem-solving abilities and have deep knowledge of advanced analytical solutions. The individual must have the ability to mentor other BIEs work with technology product development finance and business teams. The ideal candidate must have excellent communication organizational and prioritization skills with the ability to handle multiple tasks simultaneously.
Key job responsibilities
Translate business risks and needs into the development of analytics for fraud and risk detection
Coordinate with technical teams as appropriate to develop and implement analytics and reporting needs
Partner with stakeholders to gather requirements and integrate necessary data sources to support business analysis and reporting
Design and implement advanced analytical solutions. Take ownership of critical dashboards
Design optimized data loading pipelines and leverage AI to create fraud detection models
Recognize and adopt best practices for building a scalable business intelligence platform
Apply analytics and data mining techniques to solve complex problems drive business decisions and identify major gaps and opportunities
Assess trends analyzes data and proposes hypotheses to identify potential fraud patterns and financial abuse
Collaborates with the business to research develop and test new fraud detection and prevention rules
Coordinate with global team members to conduct deep dives walk-throughs and quality reviews of evidence to resolve complex problems.
Mentor and provide technical guidance to other BIEs on resolving data quality issues. Act as Subject Matter Expert when it comes to data questions.
- 5 years of analyzing and interpreting data with Redshift Oracle NoSQL etc. experience
- Experience with data visualization using Tableau Quicksight or similar tools
- Experience with data modeling warehousing and building ETL pipelines
- Experience writing complex SQL queries
- Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
- Knowledge of SQL and data warehousing concepts
- Bachelors degree in BI finance engineering statistics computer science mathematics finance or equivalent quantitative field
- Experience with AWS solutions such as EC2 DynamoDB S3 and Redshift
- Experience in data mining ETL etc. and using databases in a business environment with large-scale complex datasets
- Experience with forecasting and statistical analysis
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Required Experience:
IC
Key Skills
About Company
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