Data Scientist - Marketing Science

5 days ago

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Haus

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Haus is a marketing science platform that helps businesses measure the incrementality of their advertising efforts, both online and offline. It provides tools like GeoLift and Causal Attribution to optimize marketing campaigns and investments. Haus enables businesses to conduct experiments to evaluate the impact of their advertising spend, offering insights that drive smarter marketing decisions. By employing advanced econometric models, Haus helps companies accurately assess their marketing's incremental value, ultimately leading to better investment strategies and higher returns.

11 - 50 employees

☁️ SaaS

💰 $4M Venture Round on 2022-06

📋 Description

• About Haus • For the past 20 years, digital marketing has used your data without consent. This won’t be the case moving forward. With increasing consumer privacy, brands will need to rely on new tools to grow efficiently. Our causal inference platform gives customers the tooling they need to understand what drives their business. Whether advertising, promotions or emails, Haus helps our customers align their investment – time, money and resources – to drive incremental business outcomes. • Our team previously built these tools at industry leaders like Google, Amazon, Netflix, Lyft, and Spotify. Haus has strong customer traction and significant revenue from household name brands. Our customers rave about our solutions, and we are backed by top VCs like Baseline Ventures and Haystack.

🎯 Requirements

• 3+ Years in a Data Scientist Role • Proven track record of building and deploying data science or econometric models in production environments. • Experience in adtech or related domains (e.g., marketing measurement, media optimization) is a significant advantage. • Expertise in Causal Inference and Machine Learning • Hands-on experience with experiment design (e.g., A/B testing, quasi-experimental designs) and advanced modeling. • Familiarity with relevant frameworks (e.g., difference-in-differences, Bayesian methods, uplift modeling). • Strong Coding and Troubleshooting Skills • Proficiency in Python. • Comfort working within modern data pipelines (e.g., SQL, Spark, cloud environments). • Ability to optimize, debug, and maintain production-level code. • Effective Communication and Collaboration • History of working closely with diverse teams—product managers, engineers, external stakeholders—to drive alignment and deliver measurable results. • Comfortable explaining complex ideas to non-technical audiences and translating business needs into technical solutions. • Forward-Thinking Mindset • Keen interest in staying at the cutting edge of technology and analytics. • Self-driven approach to problem-solving, with a willingness to define questions, lead workstreams, and see them through to impactful delivery.

🏖️ Benefits

• Competitive salary and startup equity • Top of the line health, dental, and vision insurance • 401k plan • Tools and resources you need to be productive (new laptop, equipment, you name it)