Machine Learning Modeler, Advanced Insights & Modeling

Description:
• Design and implement forecasting, financial, and optimization models that support strategic decisions across Block.
• Build end-to-end machine learning pipelines for training, deployment, monitoring, and reproducible model operations at scale.
• Collaborate with data science teams to productionize experimental models and integrate them into live systems.
• Partner with analytics and finance stakeholders to ensure forecasts are interpretable, accurate, and aligned with business goals.
• Develop explainability tools that communicate model drivers, confidence, and uncertainty to stakeholders.
• Improve data pipelines and workflows using tools such as Airflow, BigQuery, and Spark.
• Establish and document best practices for model evaluation, experimentation, and maintenance.
• Translate complex technical findings into clear recommendations for non-technical partners.
• Contribute to a culture of curiosity, high-quality engineering, and continuous learning within the AIM team.

Requirements:
• 5+ years of experience in software engineering or machine learning engineering delivering production-grade ML systems.
• Deep understanding of applied machine learning and forecasting, including time-series, regression, and value prediction modeling.
• Strong proficiency in Python and ML libraries such as scikit-learn, XGBoost, LightGBM, NumPy, and pandas.
• Experience building data pipelines with Airflow, Spark, or similar orchestration tools, and working with BigQuery or other large-scale data warehouses.
• Familiarity with model explainability techniques such as SHAP, feature attribution, and uncertainty quantification.
• Excellent analytical and communication skills with the ability to connect model design to business objectives.
• Proven ability to work cross-functionally and drive high-impact results in fast-paced environments.
• Experience with forecasting or planning models in fintech, consumer, or marketplace settings.
• Exposure to automated model serving, monitoring, or feedback loops in production.
• Background in statistical modeling, uncertainty estimation, or model interpretability research.

Benefits:
• Market-based compensation with a starting salary range of $160,700 to $283,600 USD depending on location.
• Remote work flexibility.
• Medical insurance.
• Flexible time off.
• Retirement savings plans.
• Modern family planning benefits.
• Potential for other company benefits available through Block's employee benefits program.