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About Haus
Haus is a first of its kind decision science platform for the new digital privacy paradigm where data sharing and PII is restricted. Haus uses frontier causal inference based econometric models to run experiments and help brands understand how the actions they take in marketing, pricing and promotions impact the bottom line. Our team is comprised of former product managers, economists and engineers from Google, Netflix, Amazon and Meta who saw how costly it is to support high-quality decision science tooling and incrementality testing. Our mission is to make this technology available to all businesses, where all the heavy lifting of experiment design, data cleaning, and analysis/insights are taken care of for you. Haus is working with well known brands like FanDuel, Sonos, and Dr. Squatch, helping them achieve more than 30x ROI by running experiments to make more profitable decisions. We are backed by top VCs like Insight Partners, 01 Advisors, Baseline Ventures, and Haystack.
What You'll Do
You will collaborate closely with cross-functional stakeholders to understand customer problems and develop novel solutions. You will work alongside with other scientists and engineers to develop these solutions into products on our platform that will benefit our growing customer base.
The ideal candidate is a hands-on applied scientist who is excited to implement and deploy new models via scalable software solutions that drive value for customers. You thrive on execution and are able to use strong judgment and clear, succinct communication to drive the right decisions for delivering on our ambitious roadmap.
Responsibilities
- Implement innovative solutions that empower our customers to answer important business questions and drive decision-making.
- Own building solutions, models, and products while working cross-functionally with scientists and engineers to ingest customer data and deploy models and tools that deliver meaningful results on a regular cadence.
- Leverage best practices like tests, validations, monitoring, and alerting to ensure high quality experiences for a growing number of customers.
- Partner closely with Haus science and product leads to develop scalable solutions to customer problems. Enable these solutions to become core products in Haus’ product suite.
Qualifications
- MSc/PhD in Economics, Statistics, Quantitative Marketing, or equivalent industry/academic experience.
- 2+ years working in an Applied Scientist/Economist/Data Scientist role building science models and products for production environments.
- Expert in Python and SQL.
- Experience coding and troubleshooting models built for deployment.
- Experience in causal inference, statistics, and machine learning.
- Proven ability to tackle technically ambiguous problems and collaborate with cross-functional stakeholders.
- Strong communication skills with the ability to synthesize complex technical concepts concisely and precisely.
About you
- Done is better than perfect - you take small exploratory steps rather than large precise leaps toward solutions. You’re a critical thinker who enjoys pragmatically balancing technical depth vs. progressing quickly.
- Act like an owner - you take shared responsibility for team success. You bring attention-to-detail and rigor to model development and data deep dives.
- Be curious - you’re eager to test new ideas and solve novel problems.
What we offer
- 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)
Haus is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law.
Haus.io Mountain View, California, USA Office
Mountain View, CA, United States, 94043
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
