Analytical Lead

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 directly with the Heads of Science and Customer Success to scale the delivery and interpretation of statistical results from a cutting edge science platform to meet fast growing customer demands. You will serve as a trusted advisor to our customers, focusing on driving value and confidence in results. Collaborating with Customer Success, Science, Engineering, and Product teams, you will develop solutions for results robustness and communication into scalable components within a production system that will benefit our growing customer base.

The ideal candidate is somebody who is both an effective data analyst/scientist and an excellent communicator, with an appreciation for implementing best practices and communicating technical results to nontechnical audiences. You have the desire to work with nontechnical stakeholders and enjoy continually improving processes. Please apply if you want to provide real value, learn new things, and own critical components of a growing data science product.

This role is remote friendly, and hybrid compatible - we are hiring in our hubs (NYC, LA, Seattle, Bay Area), but we are remote friendly with optional in-person days (weekly) at a hub's local WeWork.

Responsibilities

• Partner closely with our customer success and science leads to identify gaps and pain points in our modeling and results delivery process.
• Serve as a trusted partner to our customers on interpretation of test results and scientific methodology, simplifying complex concepts into easy-to-understand recommendations.
• Develop and implement solutions to up-level existing workflows, visualizations, metrics to bring high-quality insights at scale to all of our customers.
• Leverage best practices like tests, validations, monitoring, and alerting, to ensure high quality outputs and experiences for a growing number of customers.

Qualifications

• Degree in Economics, Statistics, Data Science or related field
• Experience working in a Data Scientist/Analyst role
• Strong written communication and experience presenting to customers and internal stakeholders
• Experience building science models for production environments is a plus
• Experience coding and troubleshooting statistical models
• Experience working with Python and SQL.

About you

• 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.

What we offer

• Competitive salary and early 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.