Capacity Planning Analyst

Block•Saint Louis, MO

About The Position

It all started with an idea at Block in 2013. Initially built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic ecosystem, developing unique financial products, including Afterpay/Clearpay, to provide a better way to send, spend, invest, borrow and save to our 50+ million monthly active customers. We want to redefine the world’s relationship with money to make it more relatable, instantly available, and universally accessible. Today, Cash App has thousands of employees working globally across office and remote locations, with a culture geared toward innovation, collaboration and impact. We’ve been a distributed team since day one, and many of our roles can be done remotely from the countries where Cash App operates. No matter the location, we tailor our experience to ensure our employees are creative, productive, and happy. The Role We are seeking a highly analytical and data-driven Capacity Planning Analyst to optimize workforce and operational resources alignment with current and future business demands. This role leverages advanced data science techniques, including AI and machine learning, to build sophisticated forecasting models and optimize resource allocation across a 3-year planning horizon. The ideal candidate combines expertise in workforce management principles, call center operations, and advanced analytics (SQL/Python) with the ability to translate complex data into actionable business strategies.

Requirements

3-7 years of experience in capacity planning, workforce analytics, or similar analytical roles
Knowledge of WFM tools (e.g., Genesys, Verint, Assembled or specialized AI scheduling assistants). Familiarity with forecasting, staffing metrics (shrinkage, occupancy), and scheduling strategies.
SQL: Advanced proficiency for data extraction, manipulation, and analysis of large datasets
Python: Experience in data analysis, statistical modeling, and automation scripting
AI/ML: Hands-on experience with predictive models (regression, time-series analysis, forecasting algorithms)
Prompt Engineering: Experience utilizing Generative AI for automating analytical workflows and report generation
Data Visualization: Proficiency in Tableau, Looker, Power BI, or similar tools
Strong analytical and problem-solving skills with exceptional attention to detail
Excellent communication abilities to translate technical findings into business recommendations
Proven project management skills in fast-paced, multi-stakeholder environments
Strategic thinking with ability to create executive-level presentations

Responsibilities

Forecasting & Advanced Analytics Develop and maintain sophisticated capacity and demand forecasting models using historical data, market trends, and AI/ML techniques
Create statistical models for predictive forecasting with 3-year planning horizons
Conduct scenario planning and sensitivity analyses to evaluate business strategy impacts (product launches, seasonal changes, expansion)
Data Engineering & Analysis Analyze large datasets using SQL and Python to monitor KPIs, utilization rates, and identify capacity bottlenecks
Build automated data pipelines and enhance planning tools for improved accuracy and efficiency
Utilize prompt engineering with Generative AI to automate report writing and optimize query performance
Optimize queries and automate report generation using AI-powered tools
Workforce Management Strategy Apply WFM principles to forecast labor demand/supply and optimize scheduling
Manage staff allocation to meet service levels while controlling costs and preventing burnout
Monitor staffing metrics including shrinkage, occupancy, and scheduling effectiveness
Strategic Communication & Collaboration Partner with HR, Finance, Operations, Sales, and Data Science teams on capacity decisions
Transform complex datasets into compelling narratives for senior management
Present data-driven insights and strategic recommendations to executive stakeholders
Identify and mitigate risks related to capacity shortages or excesses