Onsite in Foster City, CA | at least 3 days in office
At ****, we're building the future of autonomous transportation, and data is at the heart of our mission. As a Forecaster, you will support operational teams by transforming data into insights that improve operational readiness, staffing strategies, and service performance.
In this role, you will work on operational modeling, forecasting, and decision-support analytics that help translate operational demand into resource and staffing strategies. You will analyze operational data, develop models that estimate capacity and staffing requirements, and build dashboards that provide visibility into operational performance and readiness.
Your work will support strategic and day-to-day operational decisions by translating changes in demand, staffing, and operational conditions into clear insights on capacity, operational readiness, and performance.
Key Responsibilities:
Operational Modeling: Develop analytical models that translate operational demand forecasts into resource and staffing requirements. Apply queueing and capacity models (e.g., Erlang) to estimate staffing needs, service levels, and performance under varying demand scenarios. Support capacity planning by analyzing demand patterns, service targets, and operational throughput across service and R&D testing.
Data Analysis & Reporting: Analyze operational and workforce-related datasets to identify trends, staffing gaps, and performance opportunities. Deliver reports and dashboards that provide visibility into key operational metrics.
Operational Analytics & Reporting: Provide analytical support to Operations leadership by developing models, dashboards, and insights that inform staffing strategies, operational readiness, and capacity planning. Build and maintain dashboards that track key operational performance indicators, staffing coverage, and service performance.
Data Processing & Data Quality: Use SQL and Python or equivalent to extract, clean, and transform large operational datasets from multiple systems. Ensure data accuracy and consistency across reporting and analytical models.
Operational Efficiency Analysis: Identify patterns, inefficiencies, and opportunities within operational data. Provide analysis that supports improved staffing allocation, operational coverage, and service performance.
Ad-Hoc Operational Analysis: Perform targeted analyses to support operational initiatives, evaluate staffing scenarios, and answer key business questions related to operational performance.
Qualifications:
Education: Bachelor s or Master s degree in Data Science, Statistics, Operations Research, Economics, Engineering, or a related field.
Experience
3 5 years of experience in data analysis, operations analytics, or similar analytical roles
Strong proficiency in SQL for data extraction, transformation, and analysis
Experience using Python and Pandas for data manipulation and analysis
Experience building dashboards with Looker, Tableau, Databricks, or similar visualization tools
Skills & Competencies
Strong analytical mindset with a focus on solving operational problems through data
Ability to translate complex datasets into clear, actionable insights
Ability to build analytical models that support operational planning and capacity analysis
Strong attention to detail and commitment to data accuracy
Excellent communication skills, with the ability to explain technical concepts to a diverse, non-technical audience.
Bonus Qualifications:
Experience working with Workforce Management platforms such as NICE, UKG, or similar systems
Experience building staffing models, capacity planning models, or operational forecasting models
Experience working with large-scale operational or service-based environments
Familiarity with fleet operations, service operations, or contact center environments