Block's Advanced Insights and Modeling (AIM) team is looking to develop and scale AI-driven predictive metrics that inform strategic investment decisions and drive operational excellence across the company. These metrics are foundational to planning and execution across various departments, enabling high-confidence, data-informed decisions at scale.
Requirements
- 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.
- SQL
- Python (Streamlit, Sklearn, Prefect)
- GitHub
- Databricks
Responsibilities
- Manage and participate in the development and implementation of advanced predictive models to support strategic business decisions.
- Manage project timelines and deliverables, ensuring the timely completion of data science initiatives.
- Prioritize model development efforts based on business impact and strategic objectives.
- Collaborate with machine learning engineering teams to build and maintain robust end-to-end data pipelines.
- Conduct early-stage analysis to inform model development, leveraging business intuition to suggest key drivers and features.
- Own parallel modeling to ensure alignment with business expectations and reporting.
- Interface with business stakeholders to gather requirements and ensure models meet business needs.
Other
- Bachelor’s with 8+ or Master’s with 6+ years of experience in finance, economic analysis, data science, or a related field, with a focus on applying analytic tools to business problems.
- Excellent communication skills, with the ability to convey complex technical concepts to both technical and non-technical stakeholders.
- Demonstrated ability to work collaboratively across teams and functions.
- A strong sense of business strategy, Economic insight, data science expertise, Machine Learning modeling experience, as well as project and product management skills.
- Explore improvements to business analytics using LLMs and other productivity tools.
