Machine Learning Scientist 4 - Subscription Forecasting

Netflix Netflix · Big Tech · United States · Remote · Data & Insights

Machine Learning Scientist role at Netflix focused on building and productionizing forecasting models for subscription revenue, ARPU, and member base. The role involves scenario modeling, contributing to the forecasting pipeline, and partnering with business leaders to translate model outputs into recommendations. Requires expertise in time series and regression methods, production systems, Python, SQL, and ML libraries.

What you'd actually do

  1. Build and productionize forecasting models that capture the overall trajectory of Netflix's subscription business alongside the expected impact of pricing actions on member base, ARPU, and revenue across global markets
  2. Build on the team's existing scenario modeling and simulation tools to quantify how pricing actions and broader market dynamics are expected to affect subscription metrics - giving decision-makers a way to stress-test assumptions before a pricing move happens
  3. Contribute to and advance the team's forecasting pipeline - model development, backtesting, deployment, and monitoring - and lift the accuracy and reliability of existing forecasts
  4. Partner with Finance & Strategy and Product leadership to translate forecast outputs - including their uncertainty - into concrete business recommendations

Skills

Required

  • Python
  • SQL
  • ML and statistical libraries (e.g., statsmodels, PyTorch)
  • forecasting methods (time series, regression)
  • subscription business dynamics

Nice to have

  • Advanced degree (MS or PhD) in statistics, economics, computer science, or a related quantitative field, or equivalent applied experience

What the JD emphasized

  • productionize forecasting models
  • forecasting pipeline
  • production forecasting systems

Other signals

  • forecasting models
  • subscription business dynamics
  • production forecasting systems