Senior Commercial Analytics and Data Science Manager

Senior Commercial Analytics and Data Science 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 Commercial Analytics and Data Science Manager. The successful candidate will build machine learning models, perform feature engineering to contribute to our feature store, lead dashboard development, and lead development of enhanced visualization tools.

Senior Commercial Analytics and Data Science 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.
• Be an individual contributor within a team (3–4 people), focused on research, development, and implementation of machine learning algorithms to support various business initiatives.

Senior Commercial Analytics and Data Science Manager Qualifications:

• 7+ years of experience in a 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 and libraries. Examples: CausalML/EconML, TensorFlow, PyTorch, Keras, sk-learn, seaborn, LSTM, RNN.
• Experience with visualization tools.
• Familiarity with the Databricks platform is a plus.