Point Predictive powers fraud prevention for auto and consumer lenders through the industry's largest lending fraud data consortium. When one lender sees a fraud pattern, every lender in the consortium benefits — a "herd immunity" model that stops synthetic identities, straw borrowers, income and employment misrepresentation, and dealer-facilitated fraud before they become losses. The Role This is a hybrid data analytics role and fraud strategy role combined — and we mean that as a compliment to both. You'll be the person our largest customers trust to answer the one of the most important questions in fraud prevention: "How can we improve our strategy to increase fraud capture performance while reduce false positives?" You'll dig into consortium data, customer feedback data, and portfolio performance outcomes to build, tune, and prove out fraud strategies, rules, and product utilization strategies — then walk into a room (or a Zoom) with a customer's executive team and use your comprehensive understanding of their performance and data to tell the story of what the data says, what it means, what they should do next, and do so in a way that can be understood by any executive (data and non-date first customer leaders). The best person for this job gets equal satisfaction from building a well-crafted SQL query, to utilizing cutting edge AI Agents, and a well-landed executive presentation that solves the exact needs for the customers through the power of data. If you've ever rebuilt someone's model score cutoff strategy from raw performance data and then had to defend it to a Chief Risk Officer, you know exactly what this role is. What You Will Do

▪ Own performance analytics for customer fraud strategies. Analyze feedback data — confirmed frauds, false positives, friction rates, early payment defaults, portfolio outcomes, performance drift, fraud capture rates — to measure detection performance, quantify loss avoidance, ensure product and strategy ROI, identify where strategies are leaking value, and then use your data analytics capabilities to develop a comprehensive go-forward plan that meets the unique business needs of each customer you own on the consortium.

▪ Build and tune fraud strategies. Design score thresholds, alert rules, and decisioning strategies grounded in data, balancing fraud capture against review volume and customer friction. Iterate based on what the feedback data actually shows, not what the last quarterly review assumed.

▪ Tell the story with the use of data to customer executives. Translate analysis into clear, defensible narratives for customer fraud leaders, risk executives, and C-suite audiences — in fraud QBRs, strategy sessions, proof-of-value readouts, and industry settings.

▪ Run fraud product trainings. Maintain a comprehensive understanding of Point Predictive products and provide hands-on training for customers in a variety of industries to help them better understand and utilize the technologies and strategies you developed to achieve the highest ROI and performance.

▪ Hunt patterns in consortium data. Investigate emerging fraud trends, from fraud rings, bust-out patterns, dealer-level anomalies, synthetic identity farms, country-wide fraud activity trends and turn findings into strategy recommendations and thought leadership.

▪ Work alongside AI-powered fraud tooling. Our team builds and operates AI forensic agents. You'll use them, pressure-test them, enhance them, and help shape how customers adopt AI fraud analysis.

▪ Partner cross-functionally. Work with data science on model performance, customer success on adoption and customer performance, and product on what the data says customers need next.

▪ Work with some of the leading fraud strategy experts in the industry and build out your own public brand. You will get the opportunity to work alongside some of the industry's leading fraud strategist, and will have the opportunity to speak on podcasts, keynote conferences, and build your public facing brand as a trusted source of data-backed fraud strategy for the industry, What You Bring

▪ 6+ years in fraud prevention, fraud analytics, fraud strategy, fraud data science, or closely related work — lending, banking, payments, automotive, fintech, or marketplaces. We care more about the depth of your data analytics experience and fraud (or adjacent) knowledge, not your past titles.

▪ Outstanding SQL and AI Prompt Skills. Not "familiar with." You should be comfortable writing complex queries against large datasets from scratch — joins across messy tables, window functions, cohort analysis — and know when your query is lying to you. Expect a hands-on SQL exercise in our interview process. You should also be very comfortable leveraging AI and modern technologies to help you supercharge your analytics capabilities.

▪ Proven experience building data-backed performance strategies from feedback/outcome data, performance data, or customer data: tuning rules or model score cutoffs, managing false positive rates, measuring fraud capture rates and dollar loss avoidance, and running champion/challenger comparisons will all be in your daily activities that you will need to succeed.

▪ Executive presence. You've presented analysis to senior leaders — internal or customer-facing — and can hold the room when they push back on your numbers. You can take your findings and convert them into something actionable that you can prove to others as to why your recommendation will drive higher performance.

▪ Data storytelling. You can take a 40-tab analysis and turn it into a 10-slide narrative with a clear "so what" on every slide. You are comfortable not only running your own advanced analytics to build effective fraud prevention strategies for customers, but you can then convert that into an understandable presentation to a variety of audiences, from data scientists to junior fraud analysts, to Chief Risk Officers.

▪ A strong understanding in fraud fundamentals: first-party vs. third-party fraud, synthetic identity, income/employment misrepresentation, bust-out, early payment default as a fraud signal. While having a comprehensive fraud background is not mandatory - the more fraud methodologies you understand and the faster you are able to get up to speed in this industry, the more successful you will be. Bonus Points

▪ Experience in consumer lending, experience in banking, or experience in running analytics to develop performance strategy at a fraud technology company

▪ Strong SQL experience using tools like Snowflake

▪ Have a strong foundational understanding of Machine Learning, Neural networks, and how models score applications or risk

▪ Experience with a data consortium, network, or shared-intelligence data models

▪ Hands-on experience with LLMs or agentic AI for analytical workflows

▪ Experience using, running performance analysis with, or building fraud technologies and/or vendors is a major bonus

▪ Public speaking, published analysis, or industry thought leadership can be very helpful

▪ Being able to thrive as an individual contributor while operating as a fraud strategy leader

WHAT SUCCESS LOOKS LIKE

▪ 90 days: You've mastered our data environment, own performance reporting and strategy enhancement for a set of customers and have presented your first analysis to customers.

▪ 6 months: You've independently tuned or rebuilt a customer's fraud strategy with measurable performance improvement, and customers ask for you by name.

▪ 12 months: You're a trusted fraud strategy voice — internally and with customers — and your analyses drive renewals, expansions, and product direction. Why This Team You'll join a small but industry renowned team, will be monitored and managed by some of the industry's leading subject-matter experts, and will be a key part of a team that sits at the intersection of the industry's largest lending fraud dataset in the world and its most consequential decisions. You will personally protect customers from millions of dollars in fraud losses by developing best-in-class fraud prevention and detection strategies using advanced model thresholds, rules, operation shifts, and the latest and greatest technologies. Your analysis doesn't go into a deck that dies in a shared drive — it changes how lenders stop fraud - and you'll do it while working at the

Pay:

$140,000.00 - $150,000.00 per year

Benefits:

401(k) Dental insurance Flexible spending account Health insurance Health savings account Life insurance Paid time off Vision insurance Application Question(s): Be sure the read the job description before you answer this question. Applicants that do not respond to this question, will not be considered. Please bullet out 3 prior projects you were involved in that would make you an ideal candidate for what we are looking for. The more closely your experience lines up with what we are looking for, the higher you will rank in our candidate pool. This is a required question, answering this question will make you stand out from other candidates. Our Core Values are Be The Expert, Pitch In and Get IT Done - Explain in detail how you embody these valuse and provide detailed examples from your most recent employment.

Work Location:

Hybrid remote in San Diego, CA 92101