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Principal Data Scientist

🔥 4 minutes ago

🇺🇸 United States – Remote

đź’µ $190k - $235k / year

⏰ Full Time

đź”´ Lead

📊 Data Scientist

🦅 H1B Visa Sponsor

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G2

501 - 1000 employees

Founded 2012

đź’Ľ Consulting

📣 Marketing

📦 Logistics

Consulting • Marketing • Logistics

G2 is a business software review platform that provides insights to potential buyers through over 2. 5 million real user reviews. The platform covers a wide range of software categories including project management, video conferencing, e-commerce platforms, CRM, AI chatbots, and many more. G2 empowers businesses to discover and compare software options to make informed purchasing decisions. It serves as a resource for marketers, sales professionals, IT and finance departments to optimize their software investments. Additionally, G2 offers solutions for software vendors to enhance their profiles and reach more buyers.

đź“‹ Description

• Shape how experimentation is conducted and how data science informs product decisions • Connect software vendors with the right buyers through G2 products, including ads, reviews, and agentic evaluation • Partner with stakeholders to modernize existing products and develop new products in an AEO-driven, privacy-constrained landscape • Build models, design auctions, and ship production systems as a hands-on individual contributor • Mentor team members and evangelize data science best practices across the company • Own the experimentation standard for G2 and G2 Digital Markets • Consolidate practices into a documented approach covering experiment design, randomization, metrics, guardrails, sample size, duration, and interpretation • Work with engineering teams on instrumentation, assignment, and platform behavior • Define end-to-end experimentation capability requirements, including platform, telemetry, metric layers, analysis tooling, review process, and organizational practices • Develop methods for different traffic volumes and decision speeds • Evaluate and operationalize modern experimentation methods • Teach data science across product, engineering, and business stakeholders • Improve the quality of experiment-result interpretation and communication

🎯 Requirements

• 8+ years of relevant experience in data science, applied statistics, or a closely related field, with a substantial portion focused on experimentation; or a PhD in a quantitative discipline plus 6+ years • Deep expertise in experimental design and causal inference • Working knowledge of failure modes of online controlled experiments, including power and sensitivity analysis, variance reduction, multiple testing correction, and heterogeneous treatment effects • Working command of both frequentist and Bayesian approaches • Demonstrated experience designing experimentation methodology for a real product • Track record of setting technical standards adopted by other teams • Experience influencing engineering partners without authority • Strong applied experience with time series and web/behavioral data at scale • Fluency in Python and SQL • Comfort with modern data ecosystems such as Snowflake, Spark, Airflow, and dbt • Exceptional written and verbal communication • United States work authorization without restriction; sponsorship question included in application • Preferred: 10+ years of relevant experience • Preferred: hands-on experience with modern inference methods in production • Preferred: experience with low-traffic experimentation and quasi-experimental methods • Preferred: experience with interference, network effects, or two-sided marketplace experimentation • Preferred: technical leadership, mentoring, and design/analysis review experience • Preferred: ML or LLM evaluation experience • Preferred: publications, open-source work, or conference participation • Preferred: PhD in a quantitative discipline or MS in STEM

🏖️ Benefits

• Flexible work • Ample parental leave • Unlimited PTO • Equitable and inclusive workplace • Professional growth supported by a company-wide career framework • Human oversight in hiring decisions • Option to opt out of AI-assisted application review without disadvantage

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