Data Scientist - Marketing Science

Overview: - Haus is a digital marketing platform focused on consumer privacy and efficient growth tools. - The platform offers causal inference tools for understanding business drivers. - Haus has built tools for industry leaders and has significant revenue and customer traction. Key Responsibilities: - Identify business, product, and research questions for media and advertising understanding. - Develop economic and statistical frameworks for causal inference and marketing measurement. - Test hypotheses and validate findings using advanced methodologies. - Analyze large datasets with machine learning and causal inference frameworks. - Communicate insights to technical and non-technical audiences. - Produce research documentation and knowledge-sharing materials. Requirements/Skills/Qualifications: - Proven track record in data science or econometrics, with production experience. - Experience in adtech, marketing measurement, or media optimization. - Hands-on experience with causal inference experiment design and advanced modeling. - Familiarity with difference-in-differences, Bayesian methods, and uplift modeling. - Proficiency in Python and modern data pipelines (SQL, Spark, cloud environments). - Experience working with diverse teams and explaining complex ideas to non-technical audiences. - Self-driven problem-solving and structuring unstructured problems. Compensation & Benefits: - Competitive salary range: $160,000 - $180,000 annually. - Top-tier health, dental, and vision insurance. - 401k plan. - Tools and resources for productivity. - Haus is an equal opportunity employer. (Note: The compensation details provided are based on the job description and do not include specifics on equity or additional benefits beyond the mentioned salary range.)