Full-Stack Data Scientist

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🔥 7 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

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Nimbus

WebsiteLinkedInAll Job Openings

11 - 50 employees

☁️ SaaS

🤝 B2B

Advertising Technology • SaaS • B2B

Nimbus is a disruptive new ad platform that combines the industry’s most competitive programmatic auction with comprehensive reporting. It aims to maximize ad revenue for mobile and CTV advertising by optimizing yield through agnostic auctions, low-latency cloud architecture, and real-time reporting. Designed as a 'Publisher First' platform, Nimbus connects publishers to a wide network of demand partners, ensuring the highest possible CPMs without conflicts of interest. The Nimbus platform is notable for its speed, seamless integration capabilities, and advanced ad technology like Nimbus Brain™. It serves a wide array of ad formats including video, static display, and native ads.

📋 Description

• Lead Data Analytics & Modeling: Drive data initiatives using both traditional machine learning and emergent AI technologies. Focus on pragmatic, non-generic applications that empower human decision-making and optimize our platform. • Data Pipeline Engineering: Work closely with the core engineering team to design, build, and maintain scalable data pipelines that support ML tooling, analytics, and high-velocity ad delivery systems. • Cross-Functional Collaboration: Leverage your software engineering proficiency to translate data science concepts into production-ready architecture, ensuring seamless integration between data models and backend systems. • Experimentation & Optimization: Design, evaluate, and operationalize experimentation frameworks for auction, pricing, and yield optimization. Building scalable methods to measure impact, validate model performance, and improve revenue driving decision systems. • Model Production & Monitoring: Productionize forecasting and optimization models by building backtesting, monitoring, and guardrail systems that ensure outputs are reliable, explainable, and safe to deploy in high output and delivery environments.

🎯 Requirements

• Strong data analytics capabilities with a proven track record of handling high-volume, Big Data environments. • Deep understanding of Machine Learning principles and application. • Strong understanding of AI, specifically regarding agent deployment, maintenance, and practical usage. • Hands-on experience architecting and working within cloud environments, specifically AWS. • Comfortable reading and writing production-level code. Proficiency in Python is required; experience with backend languages like Go is a significant plus. • A strong commitment to engineering best practices, including rigorous logging, documentation, and debugging. • Experience building optimization or decisioning systems in extremely high volume environments. • Excellent teamwork and communication skills, with the ability to articulate complex technical concepts to a lean, highly capable team. • A self-starter mindset with the ability to adapt to new technologies and learn quickly in a fast-paced ad-tech landscape.

🏖️ Benefits

• Fully remote work flexibility • Comprehensive health insurance packages • High level of project ownership and autonomy