Decision Engine Architect

Bachelor’s degree in computer science, Data Science, Finance, or related field (graduate degree preferred). 

Strong programming skills in SQL or Python, with experience in ETL workflows and JSON parsing. 

Experience integrating vendor APIs (including lead providers, third party data sources, fraud vendors). 

Solid background in data processing and analytics is required 

Prior experience in consumer lending, unsecured installment loans, credit risk, or acquisition funnel engineering is preferred. 

Hands-on experience with any decision engine (for example, FICO Blaze Advisor, Tekambi, Provenir, Decision Cloud, and GDS Link), scoring models, and underwriting rules is a major plus. 

Demonstrated ability to analyze funnel performance, translate insights into strategies, and optimize for both growth and scalability. 

Strong data and business intelligence (BI) reporting using industry standard BI tools such as Power BI, Tableau, Domo, and Advanced Microsoft Excel. This includes the ability to present findings to key departmental stakeholders and company executives. 

Strong communication skills, capable of bridging analytics, product, programming, data engineering, and vendor teams. 

Architect, implement, and optimize the endtoend acquisition and underwriting pipeline for unsecured installment loans. 

Build and maintain standardized data ingestion workflows, including vendor API integrations with lead providers, scoring vendors, credit bureaus, and internal sources of data (including predictive models or scores). 

Configure, test, and iterate on risk filters, decision rules, and scoring logic to balance growth, conversion, fraud mitigation, and credit quality. 

Monitor realtime pipeline performance and ensure accurate, reliable execution of all decisioning workflows. 

Analyze funnel performance and credit outcomes; translate insights into actionable strategy changes. 

Evaluate vendor performance and acquisition channels; recommend improvements and manage technical requirements. 

Develop dashboards and reporting for funnel KPIs, credit outcomes, and portfolio ROI. 

Partner with Risk, Analytics, Data Science and Engineering teams to deploy and maintain production underwriting workflows. 

Present insights and recommendations to peers and company leadership regarding decision engine performance and optimization opportunities.