Product Manager, Data Science
San Francisco, CA
Haus
Measure incrementality and allocate budget efficiently with Haus - your marketing science & experimentation platform to maximize growth.
BackgroundHaus 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.
About this roleIn this role, we’re looking for a product manager with a strong understanding of econometrics, experimentation, and statistical modeling who can partner with our team of PhD data scientists to build products which bridge the gap between scientific insight and actionable recommendations for our customers.
This PM will answer questions like: How can we translate our customers’ needs into data science questions? How can we ensure that our models produce trustworthy results for all of our customers?What data should we be collecting to improve our models?What types of interfaces should we design to help our customers interact with our models?How might we message statistical uncertainty in a way that non-technical users can understand?
About this roleIn this role, we’re looking for a product manager with a strong understanding of econometrics, experimentation, and statistical modeling who can partner with our team of PhD data scientists to build products which bridge the gap between scientific insight and actionable recommendations for our customers.
This PM will answer questions like: How can we translate our customers’ needs into data science questions? How can we ensure that our models produce trustworthy results for all of our customers?What data should we be collecting to improve our models?What types of interfaces should we design to help our customers interact with our models?How might we message statistical uncertainty in a way that non-technical users can understand?
Responsibilities
- Work with data science, engineering, sales, design, and customer success to develop a data science product roadmap
- Build products which leverage cutting-edge econometric modeling
- Perform customer discovery to uncover customer needs
- Develop systems for tracking performance and measuring success
- Become an expert in the marketing & advertising analytics ecosystem and find verticals where Haus is uniquely positioned to deliver valuable tools
Qualifications
- 5-7 years experience in Product Management or a role which requires similar skills.
- Bachelor’s degree in computer science, math, economics, statistics, finance, or a related field.
- Subject matter expertise and practical experience in at least one of the following domains: machine learning, causal inference, econometrics, statistics, or experimentation.
- Excellent communication skills, especially when translating scientific concepts for non-technical audiences.
Nice to have
- Experience building tools to analyze marketing and advertising data.
- Prior experience working as a data scientist.
- Master’s/PhD degree in statistics or related technical field.
About you
- Done is better than perfect - you take small flawed 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.
- Super organizer - You are methodical. You like to create plans and see them through execution.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Causal inference Computer Science Econometrics Economics Engineering Finance Haystack Machine Learning Mathematics PhD Privacy Statistical modeling Statistics Testing
Region:
North America
Country:
United States
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