Staff Engineer – Experimentation Team

🕒 il y a 6 mois

🇺🇸 États-Unis – Télétravail

💵 $182 600 - $295 350 / an

⏰ Temps Plein

🔴 Expert

🧑‍💻 Développeur Full-Stack

🦅 Parrain de Visa H1B

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👻 Score fantôme 31%

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🗣️🇺🇸🇬🇧 Anglais requis

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LaunchDarkly

201 - 500 employés

Fondée en 2014

💼 Conseil

🏥 Santé

📦 Logistique

💰 €200 000 000 Series D en 2021-08

Consulting • Healthcare • Logistics

LaunchDarkly est une entreprise de logiciels proposant une plateforme de gestion des fonctionnalités et d'expérimentation. Ses solutions permettent aux développeurs de contrôler les déploiements de logiciels grâce à des drapeaux de fonctionnalités, favorisant des mises en production progressives et sécurisées. La plateforme s'intègre à divers outils de développement et prend en charge plusieurs langages de programmation pour simplifier le déploiement et améliorer l'expérience des développeurs. Les solutions de LaunchDarkly s'adressent à des secteurs tels que les services financiers, la santé, la haute technologie, le commerce de détail et le gouvernement, entre autres, fournissant une infrastructure robuste qui aide à offrir des expériences utilisateur personnalisées et ciblées.

Description

• Build the experimentation statistical engine — hypothesis testing, sequential analysis, variance reduction (CUPED, Winsorization), power analysis. Ensure statistical correctness across all experiment types. • Design warehouse-native experimentation that runs analysis inside customer warehouses (Snowflake, Databricks, Redshift, BigQuery). Build modular, warehouse-agnostic abstractions for rapid new backend support. • Lead adaptive experimentation — contextual bandit systems, Bayesian optimization, automated allocation beyond simple A/B tests. • Drive the platform roadmap with product, design, and data science. Shape what we build, not just how. • Collaborate cross-functionally with Warehouse Integrations, SDK, Platform, and Data Science teams. • Mentor engineers and raise the team's bar for statistical rigor and system design. • Own operational excellence — monitoring, observability, incident response, on-call. Robust telemetry and alerting.

🎯 Exigences

• 10+ years building large-scale experimentation platforms, statistical analysis systems, or data-intensive backend services. • Applied-statistics knowledge: hypothesis testing, sequential analysis, variance reduction (CUPED), power analysis, experiment design. Comfortable with frequentist vs. Bayesian trade-offs. • Experience with adaptive experimentation ML — contextual bandits, Thompson sampling, Bayesian optimization, or RL-based allocation. • Track record designing warehouse-agnostic systems across Snowflake, Databricks, Redshift, BigQuery, or similar. • Expertise in Go, Python, or similar for backend services and statistical computation. • Experience with event-driven architectures, data pipelines, and large-scale data processing. • Cloud environments (AWS, GCP) with infrastructure-as-code. • Technical leadership: setting direction, breaking down complex problems, influencing across teams. • Ability to translate statistical concepts for product and engineering audiences.

🏖️ Avantages

• Restricted Stock Units (RSUs) • Health, vision, and dental insurance • Mental health benefits

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