Senior Manager of Commercial Analytics and Data Science

Avispa Technology•New York City, NY

10d•Remote

About The Position

A leading music streaming company seeks a Senior Manager of Commercial Analytics and Data Science. The successful candidate will play a key role in optimizing media spend through building marketing mix models and designing and measuring incrementality tests, as well as supporting test design and evaluation of marketing initiatives across multiple channels spanning the customer lifecycle.

Requirements

5+ years of experience as a Data Scientist.
Master’s degree in Data Science, Statistics, Engineering, Mathematics, or Computer Science.
Experience in paid media at large media companies
Experience building MMM models: Regression-based methods (often time-series analysis) Aggregated (non–user-level) data Support budget allocation and channel effectiveness decisions Complement incrementality testing and attribution models May involve tools such as Robyn, LightweightMMM, Nielsen, or Analytic Partners.
Experience with paid media incrementality measurement.
Strong foundation in SQL
Excellent programming skills in SQL, Python, and R.
Understanding or experience working within an enterprise data warehouse environment.
Experience building marketing mix models.
Experience working in or partnering with media agencies.
Background in subscription or e-commerce businesses.
Understanding of statistical concepts, lift analysis, and A/B testing fundamentals.
Ability to produce data visualizations for explaining technical concepts.
Experience with cloud technologies.
Familiarity with business intelligence dashboards.

Nice To Haves

Experience using tools such as Robyn and Meridian is preferred.
Experience building web apps using frameworks such as Streamlit, Shiny, or Dash is preferred.
Capability to build, tune and explain machine learning models for supervised and unsupervised learning. Methods include, but are not limited to, regression, clustering, and ensemble methods.

Responsibilities

Build marketing mix models to estimate the incremental ROI of marketing channels and optimize spend.
Design and measure paid media incrementality tests using geo-experiments.
Support testing marketing initiatives to drive app engagement and increase subscriber retention across the customer lifecycle, applying proper statistical rigor.
Build machine learning models for predicting key outcomes used to inform marketing tactics across digital acquisition and user journey orchestration.
Build web applications using Python, providing daily monitoring of test results, model results, and insights.
Develop complex SQL queries combining data from a wide variety of sources in preparation for feature engineering and test analysis.
Create custom Python libraries available for team use to automate key methods.