remote
Staff Data Scientist, Forecasting
Data Scientist
Lead advanced forecasting initiatives, building end‑to‑end pipelines with Airflow, detecting anomalies, and creating attribution models to drive data‑driven decisions.
About the role
Key Responsibilities
- Design, develop, and maintain scalable Airflow pipelines for large‑scale forecasting and anomaly detection.
- Build and validate machine learning models for forecasting, attribution, and backtesting, ensuring high accuracy and robustness.
- Conduct root‑cause analysis of model performance and data quality issues, translating findings into actionable insights.
- Collaborate with cross‑functional teams to integrate models into production systems and monitor real‑time performance.
- Mentor junior data scientists and promote best practices in model development, documentation, and reproducibility.
Requirements
- 10+ years of experience in data science with a focus on forecasting and predictive modeling.
- Proficiency in Python, Airflow, and advanced statistical/machine learning techniques.
- Strong background in anomaly detection, attribution modeling, and backtesting methodologies.
- Experience with large datasets, distributed computing, and cloud platforms (AWS, GCP, or Azure).
- Excellent communication skills and a proven track record of delivering production‑ready solutions.
Skills
pythonairflowmachine learning