Full-Time Analytics Manager
Haus is hiring a remote Full-Time Analytics Manager. The career level for this job opening is Manager and is accepting USA based applicants remotely. Read complete job description before applying.
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About HausHaus 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.
What you'll do
You will lead a team of analysts and data scientists partnering with Measurement Strategy and Product Science leaders to scale the delivery and interpretation of experiment results and insights from our cutting-edge science platform. Your team’s work will be critical to meeting growing customer demand with clarity, speed, and reliability. As a trusted leader, you will ensure customers understand and gain value from our scientific outputs, driving confidence and long-term adoption.
Working cross-functionally with Science, Engineering, Product, and Measurement Strategy teams, you will be accountable for the quality, consistency, and impact of analytical deliverables.
You’ll help translate complex statistical findings into actionable insights for customers, and ensure our processes can scale with business needs.
Responsibilities
- Lead cross-functional collaboration with Measurement Strategy, Science, and Product to identify and address gaps in how we deliver, communicate, and scale scientific results for customers.
- Design and operationalize improvements to workflows, visualizations, and key metrics that ensure consistent, scalable, and high-quality analytical outputs across the customer base.
- Guide your team in advising customers on interpreting test results and understanding scientific methodologies, translating complex analyses into clear, actionable insights.
- Recruit, coach, and develop analysts and data scientists, elevating their technical and communication skills in areas such as experimental design, validation techniques, model monitoring, and alerting best practices.
Qualifications
- Degree in Economics, Statistics, Data Science, or related field.
- 8+ years working in a Analyst/Data Scientist role
- Minimum of 3 years of experience leading analytics or data science teams, with a focus on people development and performance.
- Proven ability to manage multiple high-volume projects in fast-paced, cross-functional environments.
- Passion for building 0-to-1 systems, processes, and teams from the ground up.
- Strong customer-facing experience, with the ability to build trust and communicate technical insights to non-technical stakeholders.
- Strong technical foundation with experience reviewing and debugging analytics delivered by your team.
- Proficiency with analytical tools such as Looker, Tableau, dbt and proficient in languages such as Python and SQL. Able to support and guide team members in technical execution.
- Familiarity with marketing measurement methodologies, particularly geo-based or regional testing, is a plus.
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.