Staff Software Engineer, Planning - Data

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

If building a new product at a growing company is your desire, look no further. This role is centered on building the Causal Marketing Mixed Model, cMMM or cM3. Similar to how a hedge fund identifies an optimal mix of investments, Haus is building a machine learning-driven engine for allocating advertising investments across marketing channels like Google Ads, Pinterest Ads, TV ads, billboards, etc. to maximize customer acquisition.

We are searching for both Senior and Staff level engineers to help us build a robust and scalable data onboarding, as well as automated data ingestion pipelines to power the cMMM. You will own onboarding and analysis pipelines that will ingest customer data and deliver model results at a large scale. You will be the foremost contributor providing data operations leadership to translate model outputs into value for our customers.

The ideal candidate is somebody who is both a great software engineer and an excellent communicator, who enjoys improving existing solutions as well as designing tailored solutions for customers. 

Responsibilities

• Partner with product and science teams to understand the data needs for our new product
• Design, build, maintain, and troubleshoot data pipelines.
• Own the onboarding of data types and data providers.
• Dive deep into data discrepancies, root cause the problems, and incorporate solutions into the shared data platform to improve customer satisfaction.
• Mentor engineers on the team.

Qualifications

• 7+ years of experience as a Software Engineer.
• Experience building and deploying products that rely on large-scale distributed systems in Python or Go, Scala/Java, or other similar languages: it makes you uncomfortable deploying something for end-users without thinking about things like performance metrics, monitors and dashboards, graceful degradation and feature flags.
• Third party integrations - API are your bread and butter.
• Experience with cloud infrastructure (Google Cloud, AWS, etc).
• Experience working with SQL databases.

Bonus points

• Earlier stage startup experience.
• Experience with build systems and infrastructure management tooling like Terraform. 
• Experience with data warehouses: Snowflake, BigQuery, RedShift.
• Experience with data workflow orchestration: Dagster, Airflow
• BS/MS/PhD in Computer Science, Applied Mathematics or a related field.

What we offer

• Competitive salary and startup equity
• Top of the line health, dental, and vision insurance
• 401k plan
• Provide you with the tools and resources you need to be productive (new laptop, equipment, you name it)
• Small team with big impact on the overall output

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.