Fraud Model Consulting Lead
Leads fraud model retro-as-a-service and POC programs, partnering with customers to demonstrate ROI of fraud products and drive adoption. Collaborates between data teams and customers, interpreting ML outputs for technical and non-technical audiences; requires 5-10 years in customer-facing fintech analytics.
About the job
Responsibilities
- Own the retro and POC process end-to-end and collaborate with customers and internal stakeholders at Plaid
- Partner closely with customers to help them understand the ROI of Protect and make recommendations for implementing our fraud products
- Drive post-retro follow-through to convert retro results into production usage
- Serve as a feedback loop between customers and product to drive our Protect roadmap
Qualifications
- 5-10 years of experience in a customer-facing analytical role in fintech, financial services, or a related domain (e.g., software/tech)
- Experience working closely with data science teams
- Experience managing consultative customer engagements where you owned the deliverable and the relationship
- Comfort interpreting ML model output (e.g., precision/recall, score distributions) and explaining it to a non-technical audience
Nice to have:
- Background in data science or ML engineering, particularly on a fraud or risk team
- Experience in fraud, identity, or risk — either from a fraud prevention vendor, a fraud team at a bank or fintech, or consulting on risk engagements
Skills
Machine Learning, Data Science, Fraud Detection, Risk Management, Precision/Recall, Ml Model Interpretation, Fintech, Consultative Sales, Proof Of Concept, ROI Analysis
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