Data Scientist

We’re looking for a Data Scientist to own our machine learning sales forecasting capability end to end. You’ll design, build, and productionize forecasting models that drive planning, inventory, and revenue decisions across the business. Our data lives in BigQuery and our models are trained, served, and monitored on Vertex AI - so you’ll be working with a modern, fully managed Google Cloud stack from day one.

What you’ll do:

• Build, validate, and deploy ML-based sales forecasting models (time series, regression, and hierarchical/demand forecasting approaches) that produce accurate short- and long-horizon predictions.
• Engineer features and prepare training data directly in BigQuery, including building reusable, well-documented SQL/transformation layers.
• Train, tune, and deploy models on Vertex AI - using custom training jobs, Vertex AI Pipelines for repeatable workflows, and endpoints (or batch prediction) for serving.
• Stand up model monitoring, retraining triggers, and drift/accuracy tracking so forecasts stay reliable in production.
• Partner with Sales, Finance, and Operations stakeholders to translate business questions into forecasting problems and communicate results clearly to non-technical audiences.
• Establish forecast accuracy benchmarks (e.g., MAPE, WAPE, bias) and continuously improve on them.
• Contribute to data quality, documentation, and MLOps best practices across the team.

• 8+ years of experience as a Data Scientist or ML Engineer, with hands-on work shipping models to production.
• Strong experience with time series and/or demand forecasting methods.
• Proficiency in Python (pandas, scikit-learn, and a forecasting or deep learning library such as statsmodels, Prophet, XGBoost, or TensorFlow/PyTorch).
• Advanced SQL and real experience working in BigQuery at scale.
• Experience with BigQuery ML (BQML) for in-warehouse model training.
• Hands-on experience with Vertex AI (custom training, pipelines, model registry, endpoints, or batch prediction) or comparable cloud ML platforms with a clear willingness to work in Vertex.
• MLOps experience: CI/CD for models, Vertex AI Pipelines, experiment tracking, automated retraining.
• Solid grounding in model evaluation, validation, and the statistics behind forecasting.
• Ability to explain technical trade-offs and results to business stakeholders.