Staff Data Scientist / Machine Learning Engineer
Descripción del puesto
- Hands-on experience in Machine Learning Engineering using Python, including developing, deploying, and maintaining production-grade ML models, for 5+ years.
- Proven experience with gradient boosting algorithms (XGBoost, CatBoost, or LightGBM), including hyperparameter tuning, feature importance analysis, and advanced model evaluation.
- Strong proficiency in SQL and BigQuery, including complex feature engineering queries, scheduled data transformations, and data validation.
- Hands-on experience deploying and maintaining ML workloads on Google Cloud Platform (GCP), including Cloud Run, Airflow/Composer, Vertex AI, and Pub/Sub.
- Solid understanding of model calibration, business-oriented loss functions, and the impact of prediction errors on downstream optimization systems.
- Practical experience integrating ML model outputs with external systems through APIs, such as advertising platforms, recommendation engines, pricing systems, or bidding systems. Strongly preferred:
- Experience in e-commerce or Direct-to-Consumer (DTC) environments, particularly customer lifetime value (LTV) prediction, purchase forecasting, churn modeling, or customer segmentation.
- Familiarity with probabilistic customer models (BG/NBD, Gamma-Gamma, or similar frameworks) or strong foundations in Bayesian statistics.
- Experience with advertising platform integrations, including Google Ads API (ConversionUploadService, Enhanced Conversions), Meta Conversions API (CAPI), or similar server-side event tracking systems.
- Knowledge of identity resolution and entity matching techniques, including graph-based identity stitching, probabilistic matching, or cross-device identity resolution.
- Level of English – from Upper-Intermediate and above.