Fraud Strategist

Plaid; United States; Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Vibrant offices

Health benefits

Fertility support

Mental health support

Parental leave

Home office stipend

Daycare support

Commuting benefits

Job summary

Plaid is seeking a Fraud Strategist to mature our retro-as-a-service and POC program, translating model insights into compelling business cases for customers.

You will work between the data team and customers, ensuring adoption of our Protect products and clarity on ROI, while collaborating with stakeholders across Plaid.

Qualifications

• 5–10 years of experience in a customer-facing analytical role in fintech.
• Experience managing consultative customer engagements.
• Experience working closely with data science teams.
• Nice to have fraud, identity, or risk background.
• Nice to have ability to interpret ML model outputs.
• Background in data science or ML engineering, esp. fraud/risk.

Responsibilities

• Own the retro and POC process end-to-end and collaborate with customers and Plaid internal stakeholders.
• Partner with customers to understand the ROI of Plaid Protect and recommend fraud products.
• Drive post-retro follow-through to convert retro results into production usage.
• Serve as a feedback loop between customers and product to influence the Protect roadmap.

Skills

Customer-facing analytics

Consultative engagements

Data science collaboration

ML model interpretation

Fraud/risk experience

Data science background

Job description

• Our Fraud team’s mission is to help companies detect and prevent fraud using financial network data. We believe that transaction patterns, device signals, and behavioral data are an underleveraged tool in fraud prevention
• The Fraud Strategist is responsible for building and maturing our retro-as-a-service and POC program and driving adoption of our fraud products
• The role sits between our data team and the customer (i.e., the role will not build the models, but will need to understand the output well enough to clearly and compellingly present the business case and work with technical stakeholders and customers.)
• 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

Benefits

• Vibrant offices in SF, NYC, and Raleigh-Durham—catered meals, happy hours, and clubs to keep you connected
• Competitive pay, comprehensive health benefits, and support for fertility, mental health, and parental leave
• Lifestyle perks including home office stipends, daycare support, and commuting benefits like CitiBike and Lyft

[Nice to have] 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 Comfort interpreting ML model output (e.g., precision/recall, score distributions) and explaining it to a non-technical audienceExperience managing consultative customer engagements where you owned the deliverable and the relationshipExperience working closely with data science teams5-10 years of experience in a customer-facing analytical role in fintech, financial services, or a related domain (e.g., software/tech)[Nice to have] Background in data science or ML engineering, particularly on a fraud or risk team