Senior Data Scientist

Sphere Entertainment GroupLas Vegas, NV
17dOnsite

About The Position

The Senior Data Scientist will play a key role in building, enhancing, and maintaining advanced forecasting models to accurately predict revenue and ticket sales of future events. This position will work closely with cross-functional stakeholders to deliver actionable insights that drive strategic scheduling and event planning, ensuring optimal business outcomes.

Requirements

  • Bachelor’s degree in Data Science, Computer Science, Business Administration, or a related field.
  • 5+ years of experience in data science, data analytics, or a related field.
  • 5+ years of experience with SQL, Python or other machine learning languages.
  • Proven expertise in developing and applying machine learning algorithms and predictive modeling techniques for time series analysis and forecasting.
  • Experience incorporating exogenous variables such as weather, promotions, intellectual property popularity, competitor events and economic indicators.
  • Familiarity with seasonality patterns (day-of-week, on-sale spikes, holiday effects)
  • Excellent verbal and written communication skills, with the ability to convey complex information clearly.
  • Strong analytical and problem-solving skills with attention to detail.

Nice To Haves

  • Previous experience with AWS (e.g., S3, Sagemaker, Lambda) is a plus
  • Previous experience in Ticketing or the Sports industry is a plus

Responsibilities

  • Develop and maintain advanced forecasting models to predict revenue and ticket sales for new and upcoming events.
  • Enhance existing predictive models to improve accuracy and reliability of forecasts.
  • Communicate model performance insights, including accuracy metrics and error analysis, to stakeholders and executive leadership to drive data-informed decisions.
  • Ideate and propose innovative model features by analyzing data patterns and emerging trends to enhance predictive performance and value
  • Collaborate with business intelligence to deliver data science tools and interactive dashboards to the Revenue Management team, enabling actionable insights and data-driven decision-making.
  • Define and track key performance indicators (KPIs) to assess the effectiveness of data science initiatives.
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