Requirements

Bachelor's degree in Statistics, Mathematics, Data Science, Economics, Operations Research, a related quantitative field, or equivalent practical experience.
3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R), querying databases (e.g., SQL), or statistical analysis.
Experience in cross-functional program management, project management, or operational process execution; or managing vendor teams, operations hubs, or leading distributed operational workflows.
Experience with forecasting demand or volume in contexts like operations, contact centers, workforce management, or supply chain, or with support operations metrics (e.g., SLA, AHT, Shrinkage) and capacity planning and staffing methodologies (e.g., Erlang C).

Nice to haves

Master's degree in Statistics, Mathematics, Data Science, Economics, Operations Research, a related quantitative field, or equivalent practical experience.
Experience with advanced time-series forecasting methods (e.g., ARIMA, exponential smoothing) applied to complex operational datasets.
Experience managing vendor teams, operations hubs, or leading distributed operational workflows.
Experience building or leveraging agentic and Large Language Model (LLM)-based solutions to automate and scale analytical workflows.

Develop, tune, and review time-series forecasting models (e.g., ARIMA, Fargo) using R, Python, and SQL to accurately predict 1:1 support volumes and handle times.
Manage a growing internal operations hub handling daily forecasting execution and take technical ownership of pipeline integrity by troubleshooting errors, validating configurations, and resolving reporting issues.
Monitor model health and forecast accuracy; conduct root-cause analyses on variance and implement methodology adjustments to maintain high prediction fidelity at scale.
Partner with business and operational teams to gather forecasting inputs and deliver actionable outputs used for critical staffing and capacity decisions.
Create and leverage agentic and LLM-based solutions to automate and enhance support operations and forecasting pipelines.