Impress employers and recruiters.
Choose from hundreds of resume examples.
Impress employers and recruiters.
Choose from hundreds of resume examples.
Target Resume Now
About the Role
This role will drive high-impact projects for advanced marketing planning, analysis, and optimization at Haus using optimization, machine learning, and causal inference. The role will be a blend of working with applied scientists, data scientists, data engineers and other MLEs to deliver trustworthy results to our customers while focusing on creating processes that help scale the business.
Responsibilities
- Drive initiatives from concept to final product delivery, ensuring seamless end-to-end execution.
- Lead or contribute to the design, development, optimization, and product ionization of machine learning (ML) solutions for complex and high-impact problems.
- Implement probabilistic techniques into reusable statistical libraries, including bootstrapping, statistical tests, and ML models/regressions.
- Build and maintain the ML systems that power Haus’ product lines (specifically cMMM).
- Review code and designs of teammates, providing constructive feedback.
- Lead and collaborate with engineering and cross-functional partners across product, engineering, and science teams to drive system development from ideation to production.
- Drive design and implementation of AI (Agentic) workflows for ML pipelines (including model validation).
- Mentor ML engineers and raise the organization’s ML bar.
Requirements
- PhD or equivalent experience in Computer Science, Engineering, Mathematics or related field
- 10+ years of industry experience ideally with a focus on Machine Learning Engineer, building and operating production ML systems.
- Experience in exploratory data analysis, statistical modeling, hypothesis testing, and experimental design.
- Experience working with cross-functional teams (product, science, product ops etc).
- Proficiency in one or more object-oriented programming languages (e.g. Python, Go, Java, C++).
Skills
- Optimization
- Machine learning
- Causal inference
- Production code writing
- Scalable systems development
- cMMM machine learning
- Probabilistic techniques
- Statistical libraries
- Bootstrapping
- Statistical tests
- ML models/regressions
- ML systems
- AI (Agentic) workflows
- ML pipelines
- Model validation
- Modern deep learning architectures
- Probabilistic modeling
- Design and architecture of ML systems and workflows
- Optimization techniques
- Reinforcement learning (RL)
- Bayesian methods
- Multi-armed bandits
- MLFlow
- Data science approaches in marketing and growth
- Machine learning approaches in marketing and growth
Location
- San Francisco
- Seattle
- New York City
Work Type
- Hybrid
Experience Level
- 10+ years of industry experience
Education Level
- PhD or equivalent experience in Computer Science, Engineering, Mathematics or related field
Benefits
- Flexible PTO
- Equity
- Top of the line health, dental, and vision insurance
- WFH stipend
- Events & Offsites
- Free Lunch
- New Parent Leave
About the Company
- Haus is the causal marketing platform top businesses trust to optimize billions in ad spend worldwide.
- With support from PhD economists, data scientists, and growth experts, Haus’ AI-driven technology translates complex marketing measurement into clear action and outcomes, enabling brands like Dyson, Wayfair, Sonos, Fanduel, SharkNinja, and Intuit to optimize spend, accelerate growth, and make smarter marketing decisions at scale.
- We’re a high-performance, low-ego team operating in a fast-moving environment.
- We care deeply about our customers and expect everyone to take full ownership of their work — this is a place where high expectations fuel even higher growth.
- If you thrive in ambiguity, take pride in raising the bar, and want to work alongside top-tier peers who challenge and support you, you'll find unmatched opportunities here.
- If you're looking for predictability or rigid structure or you prefer order-taking to go-getting, we’re probably not the right fit — and that’s okay.
- We work in small, mission-driven teams that prioritize inclusion, collaboration, and growth over hierarchy or red tape.
Equal Opportunity
- Haus is an equal opportunity employer. We make hiring decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected status.
- We believe diverse perspectives make us stronger and are committed to an inclusive culture where everyone feels seen, heard, and empowered to contribute. Bring your authentic self — we would love to hear from you.