About Measured

Measured is the pioneer and leader of incrementality-based media measurement and optimization. Since 2017, leading brands have used our AI-powered, all-in-one platform to manage, test, plan, and optimize over $35 billion in full-funnel media investments. Measured’s unique combination of automated experimentation, media mix modeling, and industry-leading expertise helps marketers prove the incremental impact of their advertising and maximize ROI with unmatched ease, accuracy, and efficiency.

The Role

As a Staff Data Scientist at Measured, you will play a key role in advancing our Marketing Mix Modeling (MMM) solution and other data science-driven capabilities. You will work on developing new features and enhancements for our enterprise-grade MMM-powered platform, integrating advanced modeling techniques, automation, and causal inference methodologies to provide precise and actionable insights to our clients. Your work will include deep R&D, testing, implementation, deployment, monitoring, and internal and external support for the MMM results.

This role requires a hands-on data scientist who is customer-focused, analytically strong, and adept at problem-solving in complex data environments. You will work cross-functionally with Product, Engineering, and Customer Success teams to drive innovation in marketing measurement.

Key Responsibilities

Contribute to Measured’s advanced MMM platform that integrates media variables, pricing indices, promotional schedules, holidays, macroeconomic factors, and causal inference signals.
Develop and deploy enhancements to the MMM platform in order to answer the complex questions asked by clients.
Conduct research and development on emerging measurement methodologies and apply cutting-edge statistical and machine learning techniques.
Leverage AI capabilities and build AI tools that streamline the development and delivery of MMM results.
Optimize and automate model training, deployment, and monitoring to enable large-scale, high-frequency modeling across clients.
Collaborate with the product, design and engineering teams to integrate advanced data science solutions into the Measured platform.

Interpret complex data science outputs and translate them into actionable recommendations for marketers.
Support internal teams by providing expertise on MMM results, ensuring high confidence in model outputs and business recommendations. Also present to clients as needed.
Whatever else it takes to get the job done!

Requirements

Ideal Experience

7+ years of experience in data science, with a focus on marketing analytics, econometrics, or causal inference with 3+ years of direct experience in building MMMs or other marketing attribution models.
B.S. or higher in Mathematics, Computer Science, Statistics, Data Science, or a related quantitative field.
Proficiency in Python, SQL, and statistical modeling techniques such as Bayesian inference, regression modeling, and causal inference.
Familiarity with building scalable products, including comprehensive testing and code debugging.
Comfortable engaging directly with customers to explain methodologies, results, and recommendations
Excellent communication skills with the ability to translate mathematical concepts into business insights for technical and non-technical audiences.
Independent decision maker in an ever evolving environment. Can take calculated risks, deal with ambiguity, and suggest creative solutions to problems.
Values diversity and integrity.

Benefits

100% Remote
Competitive Total Rewards and flexible paid time off
Opportunities to give back through Measured for Good
Engaged, diverse, and curious culture
Award-winning technology powered by an agile, collaborative team

Measured values curiosity, integrity, aiming for the extraordinary, customer obsession, and employee belonging.

Measured promotes diversity and inclusivity in all forms, which helps to shape our company culture and industry leading products. Measured is committed to providing equal employment opportunities (EEO) to all employees and applicants, regardless of race, color, hairstyle, religion, sex, national origin, age, disability, genetics, or any other protected characteristics.