Block is looking for a Machine Learning Modeler to design and scale intelligent systems that power data-driven decision-making across various domains within the company, aiming to improve forecasting, financial analysis, and operational efficiency through advanced modeling and AI.
Requirements
- 5+ years of experience in software or ML engineering, with hands-on experience delivering production-grade ML systems.
- Deep understanding of applied ML and forecasting, including time-series, regression, and value prediction modeling.
- Strong proficiency in Python and common ML libraries such as scikit-learn, XGBoost, LightGBM, and NumPy/pandas.
- Experience building data pipelines using tools such as Airflow, Spark, or similar orchestration systems, and working with BigQuery or other large-scale data warehouses.
- Familiarity with model explainability techniques (e.g., SHAP, feature attribution, uncertainty quantification).
- Experience connecting model design to business objectives.
- Background in statistical modeling, uncertainty estimation, or model interpretability research.
Responsibilities
- Design and implement forecasting, financial, or optimization models that power strategic decisions across Block.
- Build end-to-end ML pipelines for training, deployment, and monitoring, ensuring reproducibility and performance at scale.
- Collaborate with Data Science to productionize experimental models and integrate them into live systems.
- Partner with Analytics & Finance teams to ensure forecasts are interpretable, accurate, and aligned with business objectives.
- Develop or contribute to explainability tools that communicate model drivers, confidence, and uncertainty to stakeholders.
- Improve data pipelines and workflows using systems like Airflow, BigQuery, and Spark.
- Establish and document best practices for model evaluation, experimentation, and maintenance.
Other
- Translate complex technical findings into clear, actionable recommendations for non-technical partners.
- Contribute to a culture of curiosity, high-quality engineering, and continuous learning within the Advanced Insights & Modeling organization.
- Proven ability to work cross-functionally and drive high-impact results.
- Experience in forecasting or planning models in fintech, consumer, or marketplace settings.
- A passion for transforming complex ML outputs into actionable insights and tools for decision-makers.
