Block is looking to pioneer the design of intelligent systems that power the future of decision-making across the company, spanning Cash App, Square, and Corporate domains such as Treasury, Cost, and Accounting, by developing AI-driven, self-adaptive models that forecast, reason, and act.
Requirements
- 8+ years of experience in machine learning or software engineering, with proven experience leading large-scale ML projects.
- Deep expertise in forecasting, predictive modeling, and value estimation, including statistical and ML-based methods.
- Advanced proficiency in Python, and experience with libraries such as scikit-learn, XGBoost, LightGBM, and pandas/numpy.
- Strong experience building end-to-end ML pipelines, leveraging tools like Airflow, Spark, BigQuery, or equivalent systems.
- Demonstrated success in designing systems that support explainability, reproducibility, and operational reliability.
- Strong understanding of data modeling, feature engineering, and model evaluation in production contexts.
- Experience with forecasting frameworks (e.g., Prophet, statsmodels, or custom time-series methods).
Responsibilities
- Lead design and implementation of forecasting, financial, and cost modeling systems that inform company-wide decisions.
- Develop scalable ML architectures and pipelines for training, serving, and monitoring predictive models.
- Build and extend AI tools for model explainability and interpretability, making predictions accessible to Finance, Analytics, and Product teams.
- Partner with Data Science to operationalize research models, ensuring performance, reliability, and reproducibility.
- Collaborate with Forecasting Analytics and Corporate Finance teams to deliver insights that guide resource allocation and financial planning.
- Define technical standards, best practices, and frameworks for applied ML development across business lines.
- Lead the architecture and delivery of AI-driven, self-adaptive models that forecast, reason, and act—shaping how Block allocates resources, scales growth, and plans for the future.
Other
- 8+ years of experience in machine learning or software engineering.
- Experience mentoring engineers and shaping team-wide technical direction.
- Background in financial modeling, planning, or customer lifetime value prediction.
- Experience building automated or interactive explainability systems for ML-driven forecasts.
- U.S. roles are typically open for an average of 55 days before being filled by a successful candidate.
