Senior Data Scientist

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Company Overview

A marketing intelligence technology company that provides eCommerce brands with a unified view of their business data through advanced attribution modeling, measurement solutions, and customizable dashboards. Its technology uses machine learning and first-party data to help businesses measure advertising performance, understand customer journeys, and improve growth decisions. The company is expanding its AI capabilities to help organizations operationalize data insights and automate decision-making.

Responsibilities

• Build, deploy, and maintain production systems supporting marketing measurement products, including marketing mix modeling (MMM), incrementality, insights, and recommendation systems.
• Translate statistical and causal inference methodologies into scalable, reliable, customer-facing capabilities.
• Improve the accuracy, coverage, reliability, and operational robustness of measurement systems.
• Debug data, modeling, and production issues across the full technology stack, from source data and pipelines to customer-facing outputs.
• Evaluate methodological improvements while balancing statistical rigor, implementation complexity, maintainability, and business value.
• Partner with Data Science, Engineering, Product, and Customer Success teams to improve measurement quality and product capabilities.
• Explain statistical concepts and measurement methodologies to customers, troubleshoot measurement-related issues, and incorporate customer feedback into product improvements.
• Own projects across the full lifecycle, including methodology evaluation, model development, implementation, deployment, monitoring, and operational support.

Qualifications

• Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, or another highly quantitative field; a Master’s degree or PhD is preferred.
• 5+ years of experience building and deploying data science, machine learning, or AI systems in production environments.
• Strong foundation in statistics, machine learning, experimentation, and causal inference, with experience applying these methods to real-world business problems.
• Strong coding and debugging skills, with the ability to write maintainable, testable, and reliable production-quality code.
• Experience implementing, deploying, and supporting statistical or machine learning systems in production.
• Ability to troubleshoot issues across the full stack, including source data, data pipelines, model logic, production services, and customer-facing outputs.
• Experience owning projects end-to-end, from problem definition and methodology evaluation through production deployment and operational support.
• Ability to work effectively in a fast-paced startup environment and drive projects from concept through production with a high degree of autonomy.
• Strong communication skills and the ability to explain technical concepts to both technical and non-technical audiences.
• Growth mindset, intellectual curiosity, and willingness to learn new domains, technologies, and measurement methodologies.

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