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.

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.