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Data Science Leader

2 months ago


Mountain View, California, United States 01 Advisors Full time

About Haus

Haus is a pioneering platform for the digital age, where data sharing and sensitive information are restricted. We leverage cutting-edge causal inference models to run experiments, enabling brands to understand the impact of their marketing, pricing, and promotional strategies on their bottom line.

Our team comprises seasoned professionals from Google, Netflix, Amazon, and Meta, who recognized the need for accessible decision science tools. Our mission is to empower businesses with high-quality decision-making capabilities, streamlining experiment design, data cleaning, and analysis.

We partner with prominent brands like FanDuel, Sonos, and Hims & Hers, achieving up to 30 times return on investment by running experiments and informing data-driven decisions.

Job Overview

As a Senior Data Scientist / Applied Economist, you will lead the development of predictive models, collaborate with engineers to integrate customer data, and deploy models that deliver exceptional results for our expanding client base. You will be responsible for advancing the GeoLift model, focusing on feature enhancements for accuracy, scalability, and business impact.

You will drive experimentation and A/B testing methodologies, ensuring rigorous statistical evaluations of business outcomes. Additionally, you will provide scientific leadership, cultivating a robust knowledge base in causal modeling and mentoring a growing team of scientists.

Responsibilities

  • Partner closely with our Customer Success team and science/product leads to answer questions, identify gaps, and find opportunities to improve our products.
  • Develop scalable solutions to enable customers to clearly interpret results, gain insights, and drive business decision making.
  • Own building solutions, models, and products, working cross-functionally with scientists, designers, and engineers to ingest customer data and deploy models/tools delivering meaningful results on a regular cadence.

Qualifications

  • MSc/PhD in Economics, Statistics, Quantitative Marketing, or equivalent industry/academic experience.
  • 5+ years working in a Data Scientist role building science models/products for production environments.
  • Proven experience in causal inference, statistics, and machine learning.
  • Demonstrated ability to work with customers and/or cross-functional stakeholders.
  • Experience coding and troubleshooting models built for deployment.
  • Experience working with Python and SQL.

Salary and Benefits

The estimated salary range for this position is $170,000 - $190,000 annually. Our benefits package includes competitive salary, top-tier health insurance, 401k plan, and comprehensive tools/resources to support your success.