Machine Learning Data Scientist - Consumer Forecasting

What you'll do

• Build and operate forecasting models and systems across product, finance, infrastructure, and go-to-market domains.
• Own the modeling lifecycle, from scoping and development through deployment, monitoring, and explainability.
• Translate forecasts into business recommendations and integrate them into planning and decision-making.

What they ask for

• Advanced degree (MS or PhD) in a quantitative field.
• Expertise in time-series forecasting and model trade-offs across performance, explainability, and scalability.
• Proficiency in Python, SQL, and tools such as scikit-learn, PyTorch/TensorFlow, and forecasting libraries.
• Experience monitoring, debugging, and maintaining models in production.

Nice to have

• Experience building or scaling forecasting platforms in a high-growth company.
• Familiarity with causal inference or Bayesian forecasting; experience building agentic decision support systems.

Pay

$347K – $445K (base salary)

Tools

Python, SQL, scikit-learn, PyTorch/TensorFlow, TimeGPT

AI focus

Research and evaluate forecasting techniques including large language model extensions and hybrid approaches; build forecasting systems to inform strategic decisions.