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, 01 Advisors, Baseline Ventures, and Haystack.
What You'll Do
You will work with the Head of Science and lead a team of economists and applied scientists focused on advancing econometric research and developing innovative science products that directly contribute to our platform's growth. You will be responsible for driving research initiatives, implementing cutting-edge methodologies, and overseeing the development of new models and approaches. As a manager, you will mentor and guide individual contributors, ensuring their growth and alignment with organizational goals.
You will help shape the future of our platform by advancing the robustness, accuracy, and scalability of econometric models. You will also serve as a key thought leader, ensuring that new science projects align with both business needs and the latest academic research. Your ability to translate complex econometric models into actionable insights for both technical and nontechnical stakeholders will be crucial.
If you are passionate about research, eager to lead a talented team, and excited to innovate in a rapidly evolving space, this role is for you.
Responsibilities Drive research and development of new econometric models and methodologies to address business challenges and enhance our product offerings.Act as a key advisor to stakeholders, translating complex research and model results into clear, actionable recommendations while also synthesizing their feedback into feasible science development initiatives.Lead and mentor a team of data scientists, managing their day-to-day tasks, performance, and professional development.Work closely with cross-functional teams (Product, Engineering, Customer Success) to ensure that research and model development align with business objectives and are successfully integrated into the platform.QualificationsPhD in Economics, Statistics, Quantitative Marketing, or a related field.Proven experience in econometric research and statistical model development for production use cases.Demonstrated ability to manage and mentor individual contributors, fostering both technical growth and leadership skills.Strong written and verbal communication skills, with the ability to present complex research findings to both technical and nontechnical audiences.Ability to collaborate effectively with cross-functional teams, driving alignment between research projects and business needs.Experience working with Python and SQL.About youAct 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.Done is better than perfect - you take small exploratory steps rather than large precise leaps toward solutions.Experiment - you try new ideas rather than repeat known formulas.What we offerCompetitive salary and early startup equityTop of the line health, dental, and vision insurance401k planTools 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.
