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Intuit Credit Implementation Staff Analyst United States, California, Mountain View 139768712
05.09.2025
Responsibilities
- Partner with our credit strategists to design new lending products, develop automation driven underwriting policies, and drive more efficient acquisitions.
- Conduct data quality audits and assurance on implemented tags, identify data collection issues, propose improvements, and oversee their implementation.
- Evaluate all the possible data sources by exploring different products in the QuickBooks ecosystem. Plan and design together with data scientists and data engineers on our data architecture, pipeline and features.
- Be a great thought leader to ensure all the business needs are met and all corner cases are evaluated and checked in our data ETL process.
- Explore new technology shifts in order to determine how they might connect with the customer benefits we wish to deliver.
- Use cloud-based databases (e.g. S3, EMR and SageMaker in AWS, Spark) to mine massive scale transactional data to credit risk analyses and translate those into actionable business opportunities.
- Build ownership and leadership by working collaboratively with business partners (product development, product management, marketing, data engineering, compliance, underwriting team etc.) to design new products to increase our market share.
Qualifications
- MS/PhD in related fields such as Statistics, Operational Research, Industry Engineering, Computer Science etc. Or bachelor’s degree in same fields with 5+ years equivalent practical experience
- Have a track record of related work experience in data exploration and data pipeline development works under defined business scope and large-scale transactional datasets
- Experience or knowledge of the following decision platforms is beneficial but not required: Camunda, Provenir, FICO Blaze, Powercurve, SAS RTDM, Zoot, Drools, OpenCPU
- Familiarity with the concepts of business process modeling notation (BPMN) or decision model notation (DMN) is advantageous
- Proficient in data query, data processing and analytics tools (i.e. SQL/Hive/Hadoop/Tableau)
- Knowledgeable with data tools and frameworks (i.e. Python, Java, R, Spark)
- Familiar with engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code
- Detail oriented and with great vision on how to develop data-driven products
- Excellent communication skills and ability to learn fast, and confidence in taking ownership
- Able to work in a fast-paced working environment
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