The Economist/Applied Scientist will develop scalable solutions and models to address customer problems, collaborating with cross-functional teams and implementing tools for decision-making.
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.
Top Skills
Python
SQL
Similar Jobs
Food • Software
As a Senior Data Analytics Engineer, you'll manage ChowNow's data platform, build tools for data insights, and collaborate with teams to enhance data availability and accuracy.
Top Skills:
AWSDbtPythonSigma ComputingSnowflakeSQLTableau
AdTech • Digital Media • Marketing Tech
The Solutions Engineer collaborates with sales teams to provide technical support, develop solutions for customers, and enhance product implementation for ad-serving platforms.
Top Skills:
Ad-Serving PlatformsDigital Tools
eCommerce • Food • Information Technology • Mobile • Cybersecurity • App development • Big Data Analytics
The Manager Tech Lead will oversee the development of marketing automation workflows and personalization strategies, ensuring alignment with business objectives and technical requirements while managing a team.
Top Skills:
BrazeHandlebarsHubspotJinjaJSONLiquidMarketoMparticleSegmentSf Marketing CloudTealiumXML
What you need to know about the Colorado Tech Scene
With a business-friendly climate and research universities like CU Boulder and Colorado State, Colorado has made a name for itself as a startup ecosystem. The state boasts a skilled workforce and high quality of life thanks to its affordable housing, vibrant cultural scene and unparalleled opportunities for outdoor recreation. Colorado is also home to the National Renewable Energy Laboratory, helping cement its status as a hub for renewable energy innovation.
Key Facts About Colorado Tech
- Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3
- Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
- Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
- Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute