- Partner with engineering teams to build and deploy causal models into production
- Leverage existing literature and develop new science in the causal marketing measurement space
- Help drive product roadmap by clearly advocating for rigorous scientific solutions to customer pain points
- Support customers using new products post-launch
- MSc/PhD in Economics, Statistics, Machine learning, or equivalent industry/academic experience
- 2+ years working in an Economist / Data Scientist / Applied Scientist role building science models for production environments
- Experience in causal inference and machine learning
- Experience in experimental design and analysis
- Experience in Python and SQL
- Experience coding and troubleshooting models built for deployment
- Experience in hierarchical / mixed effects models
- Experience working in a startup or high-growth environment
- Experience with growth marketing, marketing measurement, or advertising platforms (e.g., Google, Meta, TikTok)
- Done is better than perfect - you take small exploratory steps rather than large precise leaps toward solutions.
- Act like an owner - you share responsibility with the team and do what you can to achieve success. You thrive in ambiguity and find ways to structure unstructured problems.
- Experiment - you try new ideas rather than repeat known formulas.
- Remote friendly, hybrid compatible - we are hiring in our science hubs (Seattle, Bay Area, Silicon Slopes area of Utah), but we are remote friendly with optional weekly in-person days at a hub's local Wework
- Competitive salary and equity
- Unlimited PTO
- Top of the line health, dental, and vision insurance
- 401k plan
- Provide you with the tools and resources you need to be productive (new laptop, equipment, you name it)
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Applied Scientist - Mountain View, United States - Haus
Description
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 Hims & Hers, and has seen more than 30x ROI by running experiments and helping brands make more profitable decisions. We are backed by top VCs like Insight Partners, Baseline Ventures, and Haystack.
What you'll do
You will work on research and development with our Future Products team, building the next generation of causal marketing measurement tools. You will be an active contributor to the full product life cycle, collaborating with engineers, product managers, and designers from inception to delivery to produce high-quality experiences for our customers.
The ideal candidate will be a hands-on economist/applied scientist, excited to both develop new methodologies and directly implement and deploy them via scalable software solutions. You're an executor and are able to use strong judgment and clear, succinct communication to drive the right decisions to deliver on an ambitious roadmap.
If you are a builder who loves the idea of redefining and pushing the boundaries of causal marketing measurement, then let's talk.
Responsibilities
Qualifications
Nice to have
About you
What we offer
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.
