Senior Business Analytics Analyst

GoDaddy · Canada, British Columbia

Hybrid Full-time Senior Data

Job Description

Location Details: British Columbia or Ontario, Remote

At GoDaddy the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.

This is a remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings.

Join our team

GoDaddy is empowering everyday entrepreneurs around the world by providing all of the help and tools to succeed online. With 20 million customers worldwide, GoDaddy is the place people come to name their idea, build a professional website, attract customers, and manage their work. Our mission is to give our customers the tools, insights and the people to transform their ideas and personal initiative into success!

We are seeking a Senior Business Analytics Analyst to own and evolve our Care demand forecasting model, which drives workforce planning, capacity decisions, and financial forecasting. This role combines strong SQL and R expertise with advanced forecasting knowledge and the ability to translate complex outputs into clear, executive-ready insights.

You will partner with leaders across Operations, Analytics, Finance, Workforce Management, and Care to ensure the model remains accurate, scalable, and aligned with business needs.

Please note:

AI will not be used to screen, assess or select applicants other than as set out in the details in the application below.
This job posting relates to an existing vacancy.

Compensation

In addition to the salary range below, the role may be eligible to participate in a discretionary cash bonus scheme that pays 15% of base salary based on individual and company performance.

Canada:$111,000-$167,000 CAD

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Benefits

Own and Evolve the Demand Forecast Model: Serve as an owner of GoDaddy’s Care demand forecasting model – maintaining accuracy, implementing improvements, and ensuring the model evolves alongside changing business conditions and priorities
Drive Model Development and Innovation: Find opportunities to improve forecast methodology, incorporate new data sources, and apply advanced statistical and machine learning techniques to increase model precision and reliability
Translate Forecast Outputs into Business Decisions: Convert complex model outputs into clear, compelling narratives for senior and executive leadership – ensuring forecast results are understood, trusted, and acted upon across the organization
Own Forecast Reporting Infrastructure: Develop and maintain the reporting and data infrastructure that supports the forecast model, ensuring scalability, accuracy, and accessibility for all internal team members
Lead Advanced Analytics Initiatives: Develop and deploy predictive models, statistical forecasts, and data-driven solutions that address high-priority business questions across the Care organization
Partner with Cross-Functional Leaders: Collaborate with finance, workforce management, operations, and Care leadership to align forecast assumptions, communicate model updates, and incorporate business context into forecast inputs
Set Analytical Standards: Establish and champion standard processes for forecasting methodology, model documentation, and analytical rigor across the analytics function
Share Knowledge and Elevate the Team: Serve as the internal subject matter expert on demand forecasting – sharing knowledge, documenting methodology, and helping team members understand and apply forecast outputs effectively
Identify and Quantify Business Opportunities: Proactively surface insights from forecast data that find opportunities for cost reduction, capacity optimization, or revenue growth
Champion AI Adoption: Lead the integration of AI tools and platforms into the forecasting workflow, setting the standard for how the team uses AI to accelerate model development and improve forecast quality
Bachelor’s/Master’s degree in Statistics, Mathematics, Economics, Finance, or a related quantitative field
Experience applying forecasting, analytics, automation, or AI-enabled workflows in a customer care, contact center, workforce management, or similarly operational environment

Requirements

7+ years of experience in analytics, forecasting, or a related quantitative field, including 3+ years of hands-on experience building, maintaining, and improving demand forecasting or predictive models in a business setting.
Advanced proficiency in SQL, including query optimization, complex joins, window functions, and stored procedures, and strong proficiency in R, or similar, for statistical modeling, forecasting, automation, production-ready analytical workflows, and using AI tools to accelerate model development.
Demonstrated experience with time series forecasting methods such as ARIMA, SARIMA, exponential smoothing, and regression-based approaches, with the ability to apply those methods to workforce planning, capacity management, or financial forecasting.
Strong executive communication, stakeholder partnership, and project management skills, including the ability to present complex forecast outputs to senior leaders, influence strategic decisions, and lead multiple high-priority projects in ambiguous environments.
Experience working in or directly supporting a customer care, contact center, or workforce management environment, with familiarity translating operational metrics into forecast assumptions and planning recommendations.