Staff Data Scientist, Product

Government Employees Insurance Company; Bethesda (MD); On-site; USD 115,000 - 230,000; Full time

Job summary

GEICO, a leading auto insurer, seeks a seasoned Senior Product Analytics professional to partner with product, engineering, and design to frame questions, design experiments, and deliver actionable insights. You will define metric frameworks, build ROI models, and mentor junior analysts while communicating findings to executives.

Experience in statistics, causal inference, and SQL/Python/R is essential. The role emphasizes cross-functional collaboration, rigorous analysis, and scalable decision

Qualifications

• Experience: 8+ years in product analytics, decision science, data science, or a closely related quantitative role at a technology company, with a track record of influencing product decisions.
• Experimentation: Strong background designing well-powered A/B tests, diagnosing bias and variance issues, handling interference and non-stationarity, and interpreting results under real-world conditions.
• Statistics & Causal Inference: Solid applied statistics foundation with practical experience selecting the right causal method for the question at hand.
• Tools: Advanced SQL and working proficiency in Python or R for analysis, modeling, and reproducible workflows.
• Product Sense: Demonstrated ability to define metric frameworks for a product area, not just operate within frameworks built by others.
• Communication: Clear writing and direct storytelling with data—can produce a one-pager that moves a roadmap and present to executives without losing the nuance.
• Quality Mindset: Disciplined about quantifying what you know, surfacing what you don't, and resisting false precision.
• Education: Bachelor's degree or higher in statistics, economics, computer science, mathematics, operations research, or a related quantitative field—or equivalent practical experience.

Responsibilities

• Strategic Partnership: Embed with product, engineering, and design leaders as a decision partner—framing ambiguous business questions, pressure-testing roadmap assumptions, and shaping bets before they are committed.
• Metric Frameworks: Define goal metrics, guardrails, and supporting metric trees for your product area. Decompose top-line outcomes into measurable inputs that teams can move.
• Experimentation: Design, power, and analyze A/B and quasi-experiments. Go beyond average treatment effects to understand heterogeneity, long-term impact, novelty effects, and cross-surface interactions.
• Causal Inference: Apply causal methods (difference-in-differences, synthetic control, instrumental variables, propensity scoring, switchback designs) where randomization is not feasible.
• Decision Modeling: Build opportunity sizing, forecasting, and ROI models that scale how the organization makes trade‑offs—pricing, growth, retention, and long‑range investment decisions.
• Deep Dives: Lead root‑cause investigations into user behavior, funnel performance, retention, and engagement. Translate messy signal into clear, defensible recommendations.
• Collaboration: Serve as trusted analytics partner to PMs, designers, and engineers—translate product questions into research designs, analyses, and deliverables.
• Communication: Present findings and recommendations to senior leadership with clarity, structure, and its uncertainty.
• Mentorship & Best Practices: Mentor junior data scientists and analysts. Define internal standards for experiment design, statistical rigor, and reproducible analysis.

Skills

Experience in product analytics

Experimentation design

Statistics & causal inference

SQL

Python or R

Product sense

Communication

Education

Bachelor's degree or higher in statistics, economics, computer science, mathematics, operations research, or related quantitative field

Tools

Python

R

Job description

Why Join GEICO? At GEICO, we offer a rewarding career where your 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.

Job Responsibilities

• Strategic Partnership: Embed with product, engineering, and design leaders as a decision partner—framing ambiguous business questions, pressure-testing roadmap assumptions, and shaping bets before they are committed.
• Metric Frameworks: Define goal metrics, guardrails, and supporting metric trees for your product area. Decompose top-line outcomes into measurable inputs that teams can move.
• Experimentation: Design, power, and analyze A/B and quasi-experiments. Go beyond average treatment effects to understand heterogeneity, long-term impact, novelty effects, and cross-surface interactions.
• Causal Inference: Apply causal methods (difference-in-differences, synthetic control, instrumental variables, propensity scoring, switchback designs) where randomization is not feasible.
• Decision Modeling: Build opportunity sizing, forecasting, and ROI models that scale how the organization makes trade‑offs—pricing, growth, retention, and long‑range investment decisions.
• Deep Dives: Lead root‑cause investigations into user behavior, funnel performance, retention, and engagement. Translate messy signal into clear, defensible recommendations.
• Collaboration: Serve as trusted analytics partner to PMs, designers, and engineers—translate product questions into research designs, analyses, and deliverables.
• Communication: Present findings and recommendations to senior leadership with clarity, structure, and its uncertainty.
• Mentorship & Best Practices: Mentor junior data scientists and analysts. Define internal standards for experiment design, statistical rigor, and reproducible analysis.

Basic Qualifications

• Experience: 8+ years in product analytics, decision science, data science, or a closely related quantitative role at a technology company, with a track record of influencing product decisions.
• Experimentation: Strong background designing well‑powered A/B tests, diagnosing bias and variance issues, handling interference and non‑stationarity, and interpreting results under real‑world conditions.
• Statistics & Causal Inference: Solid applied statistics foundation with practical experience selecting the right causal method for the question at hand.
• Tools: Advanced SQL and working proficiency in Python or R for analysis, modeling, and reproducible workflows.
• Product Sense: Demonstrated ability to define metric frameworks for a product area, not just operate within frameworks built by others.
• Communication: Clear writing and direct storytelling with data—can produce a one‑pager that moves a roadmap and present to executives without losing the nuance.
• Quality Mindset: Disciplined about quantifying what you know, surfacing what you don't, and resisting false precision.
• Education: Bachelor's degree or higher in statistics, economics, computer science, mathematics, operations research, or a related quantitative field—or equivalent practical experience.

Preferred Qualifications

• Advanced Methods: Bayesian methods, hierarchical models, sequential testing, or uplift modeling experience.
• Domain Experience: Background in growth, pricing, monetization, marketplace, or recommendation problem spaces.
• ML Partnership: Experience working alongside ML engineers on production models, including offline evaluation, online metrics, and guardrails.
• Platform Contributions: Contributions to internal experimentation platforms, metric stores, or measurement tooling.
• Education: MS or PhD in a quantitative discipline.
• Industry: Insurance or financial services experience.

Annual Salary $115,000.00 - $230,000.00

The above annual salary range is a general guideline. Multiple factors are taken into consideration to arrive at the final hourly rate/ annual salary to be offered to the selected candidate. Factors include, but are not limited to, the scope and responsibilities of the role, the selected candidate’s work experience, education and training, the work location as well as market and business considerations. GEICO will consider sponsoring a new qualified applicant for employment authorization for this position.

The GEICO Pledge: Great Company: Protecting customers through life’s twists and turns with innovation and integrity. Great Careers: Personalized development programs, mentorship, and certification assistance. Great Culture: Inclusive and collaborative culture rooted in shared success. Great Rewards: Competitive pay, benefits, and flexibility to support your well‑being and future.

The equal employment opportunity policy of the GEICO Companies provides for a fair and equal employment opportunity for all associates and job applicants regardless of race, color, religious creed, national origin, ancestry, age, gender, pregnancy, sexual orientation, gender identity, marital status, familial status, disability or genetic information, in compliance with applicable federal, state and local law. GEICO hires and promotes individuals solely on the basis of their qualifications for the job to be filled.

GEICO reasonably accommodates qualified individuals with disabilities to enable them to receive equal employment opportunity and/or perform the essential functions of the job, unless the accommodation would impose an undue hardship to the Company. This applies to all applicants and associates. GEICO also provides a work environment in which each associate is able to be productive and work to the best of their ability. We do not condone or tolerate an atmosphere of intimidation or harassment. We expect and require the cooperation of all associates in maintaining an atmosphere free from discrimination and harassment with mutual respect by and for all associates and applicants.

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