Staff Applied Research Scientist - Fraud Detection

GEICO•Palo Alto, CA

7d•Onsite

About The Position

We are seeking a highly experienced and strategic Staff Applied Research Scientist to lead the technical architecture and delivery of AI solutions that span multiple functional and technical boundaries at GEICO. As part of the AI Research team, you will define and own the vision for scalable, robust, and compliant AI/ML solutions; drive high-visibility, cross-functional initiatives from ideation through production; and mentor talent while aligning AI investments with business outcomes. You will drive innovation and operational excellence in fraud risk modeling by developing advanced AI solutions that enhance the detection, prevention, and investigation of fraudulent activities. Your work will focus on designing and implementing models that identify and mitigate fraud not only in insurance claims, but also across payment processing, underwriting, policy management, and customer service interactions. By leveraging state-of-the-art machine learning and large language models, you will help GEICO proactively safeguard transactions and operational processes, ensuring comprehensive protection against fraud throughout the organization.

Requirements

BS in Computer Science, Machine Learning, Statistics, Mathematics, or a related quantitative field, PhD is preferred.
At least 6+ years of professional experience delivering applied AI/ML solutions in production, including leading cross-functional initiatives with enterprise impact.
Proven expertise in leveraging machine learning, large language models (LLMs), and agentic AI systems to design, develop, and deploy advanced fraud detection and prevention solutions.
Experience includes building models for identifying and mitigating fraudulent activities as well as operationalizing AI to enhance fraud risk management and investigation effectiveness.
Strong proficiency in Python and SQL; deep experience with ML frameworks such as PyTorch, TensorFlow, and Scikit-learn
Demonstrated experience establishing KPI frameworks, experimentation, and causal analysis to quantify model impact and inform prioritization.
Excellent stakeholder management skills with a track record of driving alignment and adoption across product, engineering, and business teams.
Strong written and verbal communication skills; ability to set the right context and explain complex technical topics to varied audiences, including executives.

Nice To Haves

Experience with GenAI and LLMs (e.g., prompt design, RAG, evaluation strategies, guardrails, red-teaming, human-in-the-loop workflows).
Research experience in computer science, statistics, machine learning, operations research, or related fields; record of patents, publications, or impactful open-source contributions.
Familiarity with insurance operations and model governance in regulated environments.

Responsibilities

Identify High-Impact Opportunities: Proactively surface and shape high-value AI/ML initiatives by engaging with product, engineering, and operations to align technical roadmaps with strategic business goals.
Architecture & Technical Direction: Provide architectural leadership for AI/ML solutions impacting multiple stakeholders. Establish standards for scalability, reliability, observability, compliance, and cost efficiency across online and batch systems.
Development & Productionization: Lead end-to-end delivery of AI/ML solutions, including model design, data pipelines, feature stores, evaluation, deployment, A/B testing, and monitoring in real-time and batch environments. Ensure clear plans, milestones, and on-time delivery.
ROI Measurement & Experimentation: Establish robust mechanisms to quantify business impact, including KPI definition, experimentation frameworks, and causal inference approaches to guide decision-making and prioritize investments.
Innovation & Research Integration: Stay current with cutting-edge research in ML, GenAI, and optimization. Prototype and harden novel techniques that push the boundaries of innovation within GEICO’s insurance ecosystem. Set technical direction for multi-quarter research initiatives; build evaluation frameworks, ensure reproducibility/responsible AI, and drive cross-functional adoption; shepherd patents.
Cross-Functional Collaboration: Champion collaboration across Product, Engineering, Data Platform, Governance, Legal, and Operations to ensure responsible, compliant, and effective adoption of AI systems.
Mentorship & Capability Building: Mentor junior and senior scientists, elevate technical standards (coding, testing, documentation, reproducibility), and foster a culture of scientific rigor and engineering excellence.
Communication & Executive Engagement: Translate complex technical topics into clear narratives for technical and non-technical audiences. Present to senior stakeholders, set context, explain trade-offs, and build alignment and enthusiasm.
Lead the design and implementation of AI-driven fraud detection and prevention solutions within the car insurance domain, leveraging both machine learning (ML) and large language models (LLMs), including agentic AI systems.
Develop and deploy models that identify and mitigate fraudulent activities not only in claims but also across operational processes, such as underwriting, policy management, and customer service interactions.
Collaborate with cross-functional teams to operationalize AI for comprehensive fraud risk management, enhancing detection accuracy, streamlining investigations, and improving operational efficiency throughout GEICO’s insurance ecosystem.