Senior Applied Research Scientist

GEICO•Bethesda, MD

23h•Onsite

About The Position

GEICO is seeking a highly skilled Senior Research Scientist with a strong technical background and proven expertise in machine learning and artificial intelligence. As the AI Research team at GEICO continues to grow, you will serve as a tech lead driving end-to-end AI initiatives —from problem framing and experimentation to production deployment and adoption. You will set technical direction, architect scalable solutions, and mentor juniors while partnering closely with product, engineering, and domain experts to deliver measurable business impact. GEICO offers a rewarding career where ambitions are met with endless possibilities. Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive on relentless innovation to exceed our customers' expectations while making a real impact on local communities nationwide. Founded in 1936, GEICO is a member of the Berkshire Hathaway family of companies and one of the largest auto insurers in the United States. When you join our company, we want you to feel valued, supported, and proud to work here. That's why we offer the GEICO Pledge: Great Company, Great Culture, Great Rewards, and Great Careers.

Requirements

Master’s or PhD in Computer Science, Machine Learning, Statistics, Mathematics, or a related quantitative field, or equivalent practical experience.
3+ years of experience developing, deploying, and operating AI/ML models in production.
Strong proficiency in Python, data processing, and SQL, and in AI/ML frameworks such as PyTorch and Scikit-learn.
Experience designing online experiments and conducting causal analyses; demonstrated ability to define, instrument, and monitor business KPIs.
Proven experience leading end-to-end AI/ML initiatives and partnering cross-functionally with product and engineering.

Nice To Haves

Experience with the design, development, and optimization of high-quality prompts and templates that guide the behavior and responses of LLMs.
Experience with GenAI quality management, including evaluators, red-teaming, guardrails, and human-in-the-loop systems.
Familiarity with insurance operations and model governance in regulated environments.

Responsibilities

Lead the design and delivery of ML and GenAI solutions for complex, ambiguous, cross-functional problems.
Define success metrics, validation plans, and pathways to production.
Partner with product, engineering, and domain experts to translate business needs into feasible technical roadmaps, de-risking assumptions and aligning milestones to outcomes.
Design online experiments and quasi-experimental analyses; instrument and monitor business KPIs to quantify value and inform decision-making.
Mentor junior scientists and engineers, share best practices, and cultivate a high bar for scientific rigor, coding standards, and reproducibility.
Communicate approach, trade-offs, and results to technical and non-technical audiences; provide realistic estimates and influence decision-making across the organization.