Software Engineer - Science Platform (BE) - New York

About

Haus is the incrementality platform leading brands trust to optimize billions in ad spend worldwide. Using frontier causal inference-based econometric models to run experiments, we help brands measure the business impact of marketing, pricing, and promotions with scientific precision.

Role

You'll build and maintain the platform that powers how the world's leading brands measure the true causal impact of their marketing spend. Our Science Platform runs geo-based experiments across 100+ customers, processes daily analysis pipelines, and delivers statistical results that directly drive budget decisions worth millions of dollars. This is a backend and platform engineering role.

What You’ll Do

• Build and evolve the data pipelines that fetch, aggregate, and transform KPI data from BigQuery across multiple geographies and granularities
• Extend and maintain the statistical estimation library — implement new estimators, improve standard error methods, and optimize performance for large panel datasets
• Improve the Metaflow-based analysis orchestration system that schedules and executes thousands of daily experiment analyses on Kubernetes
• Design for reliability: build monitoring, alerting, and self-healing patterns for pipelines that run autonomously every day
• Collaborate closely with applied scientists to translate research prototypes into production-grade code with proper testing, error handling, and observability
• Work with product engineers to ensure analysis results are published correctly and flow cleanly into the customer-facing API and frontend
• Use AI development tools as part of your daily workflow to accelerate delivery and explore solutions
• Participate in on-call rotation and own the operational health of the science platform systems

Qualifications

• 4+ years of experience building and shipping production software systems
• Strong Python proficiency — you write clean, well-tested Python and are comfortable with the ecosystem (pandas, numpy, pytest, poetry)
• Experience with data-intensive applications: you've worked with large datasets, data pipelines, or ETL systems and understand the tradeoffs
• Experience with SQL and analytical databases (BigQuery, Snowflake, or similar) — you can write performant queries and understand how warehouse-scale data processing works
• Comfort with cloud-native environments (GCP preferred): you understand how to deploy, monitor, and operate services in production
• Experience with workflow orchestration frameworks (Metaflow, Airflow, Dagster, Prefect, or similar) is a strong plus
• Track record of working effectively with AI development tools (Claude, Cursor, Copilot, or similar) — you've integrated them into your workflow and can articulate how they change the way you build software
• Able to collaborate productively with scientists and researchers — you don't need a PhD, but you should be comfortable reading statistical code, understanding experimental design concepts, and asking good questions
• Excellent communication skills — you can explain technical tradeoffs clearly and work effectively across disciplines

Bonus Points

• Earlier stage startup experience
• Familiarity with statistical or scientific computing (scipy, scikit-learn, Bayesian methods) — enough to be a productive partner to scientists
• Experience with Kubernetes and containerized workloads
• Experience with event-driven architectures (Pub/Sub, message queues)
• Experience working across multiple interconnected repositories with coordinated release cycles

We Offer

• Flexible PTO - take time when you need it!
• Equity – Startup environment with part-ownership in our successes
• Top of the line health, dental, and vision insurance - multiple plan options so you can pick what fits you best
• Free Lunch – Grab a bite on us when you choose to work from the office (hub locations include SF, NYC and Seattle)
• New Parent Leave – take time to welcome your newest Hausmate

What We Value

• Inclusive culture where everyone feels seen, heard, and empowered to contribute
• High performance and low ego team operating in a fast-moving environment
• Ownership of work and taking full responsibility for your contributions

Benefits

• Bring your authentic self — we would love to hear from you.