Sr. Data Scientist, Paid Media

Burtch Works
United States
10 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Testing (Software) A/B Testing Cloud Database Data Mining Python (Programming Language) Machine Learning SAS (Software) SQL Databases Freeform SQL Feature Engineering Information Technology

Job description

The Senior Manager, Commercial Analytics & Data Science is an individual contributor role responsible for applying statistical modeling, experimentation, and machine learning to optimize marketing performance. This position focuses on measuring media effectiveness, designing incrementality tests, and developing marketing mix models that guide marketing investment decisions across the customer lifecycle., * Build and maintain marketing mix models to estimate incremental ROI and optimize media spend.

  • Design and evaluate paid media incrementality testing programs, including geo and matched-market experiments.
  • Develop machine learning models to predict marketing and subscription outcomes across acquisition and retention journeys.
  • Design and analyze controlled experiments, including sample sizing, measurement strategy, and evaluation.
  • Partner with marketing stakeholders to translate business questions into statistical analyses and actionable recommendations.
  • Deliver presentations explaining results, implications, and recommendations to technical and non-technical stakeholders.
  • Collaborate with engineering teams to productionize and monitor model performance.
  • Write complex SQL queries to prepare datasets for feature engineering and test analysis.
  • Build Python-based tools and libraries to automate analysis and testing workflows.
  • Support cross-functional teams by providing insights that influence media investment and marketing strategy.

Requirements

You will work hands-on with Python, SQL, and cloud data environments to build models, analyze results, and communicate business implications to stakeholders. The ideal candidate combines strong data science skills with business acumen and a deep understanding of paid media performance and conversion drivers., * Master’s degree in Data Science, Statistics, Mathematics, Engineering, Computer Science, or related quantitative field preferred (relevant experience may substitute)., * 5+ years of hands-on data science experience.

  • Experience working with paid media performance data, ideally within a media agency or subscription-based business.
  • Experience designing and measuring incrementality testing and experimentation programs.
  • Experience building and deploying traditional machine learning models (not generative AI focused).
  • Experience working in cloud-based data environments.

Skills

  • Strong Python proficiency (team primarily codes in Python; SAS experience alone will not be sufficient).
  • Strong SQL for data extraction and validation.
  • Experience with marketing mix modeling frameworks (e.g., Robyn, Meridian, or similar).
  • Understanding of causal inference, A/B testing, and statistical modeling techniques.
  • Ability to communicate complex findings clearly to business stakeholders.
  • Collaborative mindset and ability to work independently in a cross-functional environment.

About the company

We are a large-scale subscription media organization that relies heavily on advanced analytics and experimentation to guide marketing investment and growth strategy. The Commercial Analytics & Data Science team partners directly with marketing, finance, and product stakeholders to determine how and where marketing dollars should be deployed. The team’s work directly influences media investment decisions, customer acquisition strategy, and long-term subscriber growth.

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