Senior Marketing Analytics Manager

Senior Marketing Analytics Manager 1654-1

• Hourly pay: $80-$100/hr
• Worksite: Leading music streaming company (New York City, NYC 10020 or Washington, DC 20002 - Open to Remote Candidates located in the United States, Must work Eastern office hours)
• W2 Employment, Group Medical, Dental, Vision, Life, Retirement Savings Program, PSL
• 40 hours/week, 6 Month Assignment, Possible extension

A leading music streaming company seeks a Senior Marketing Analytics Manager. The successful candidate will lead advanced analytics and machine learning initiatives to optimize marketing performance, inform business strategy, and deliver data-driven insights through predictive modeling, A/B testing, and visualization.

Senior Marketing Analytics Manager Responsibilities:

• Build advanced machine learning models to inform marketing tactics (examples: adaptive clustering, reinforcement learning, regression modeling, price elasticity modeling etc.)
• Execute sophisticated quantitative analyses and descriptive modeling to answer key business questions to shape business strategy.
• Use enhanced python based graphical visualizations to deliver key insights to leadership.
• Research and implement novel modeling techniques to solve complex business problems.
• Develop analytics databases & lead development and maintenance of automated dashboards for AB experiment results.
• Develop complex SQL queries combining data from a wide variety of sources in preparation of feature engineering or to perform analysis of business questions.
• Measure the incrementality of paid media campaigns using matched market testing.

Senior Marketing Analytics Manager Qualifications:

• 7+ years of experience in the related field.
• Bachelor’s or Master's degree in data science, computer science, statistics, engineering, or a related quantitative field.
• Strong prior experience in data science, business & statistical analytics.
• Strong background in SQL & Python, R is a plus.
• Experience in machine learning algorithms & libraries. Examples: CausalML/EconML, TensorFlow, PyTorch, Keras, sk-learn, seaborn, LSTM, RNN.
• Experience in visualization tools. Examples: Databrick AI/BI, Rshiny, Dash, Tableau.
• Familiarity with the Databricks platform is a plus.
• Willingness to take initiative and to follow through on projects.
• Excellent time management skills with the ability to prioritize and multitask, and work under shifting deadlines in a fast-paced environment.