Job Description:
• Own short-term, mid-term, and long-term demand forecasting across all Global Operations teams and channels (phone, messaging, email, back-office etc.).
• Design, develop, and maintain statistically robust demand forecasting models using time series and machine learning techniques (e.g., exponential smoothing, ARIMA, regression-based models etc.).
• Perform trend, seasonality, and variance decomposition; detect structural breaks, outliers, and demand anomalies.
• Quantify forecast uncertainty through confidence intervals, error distributions, and bias analysis.
• Lead scenario modeling for peak demand periods, product launches, growth initiatives, and unplanned demand events.
• Continuously assess model performance using statistical accuracy metrics (MAPE, RMSE, MAE, bias etc).
• Establish model governance standards, including documentation, validation, back-testing, and post-mortem analysis.
• Research, prototype, and implement new forecasting and optimization techniques as business needs evolve.
• Perform scenario planning and sensitivity analysis to quantify trade-offs between service levels, cost, and utilization.
• In partnership with the Analytics and Data Engineering team, design and build scalable planning data pipelines, dashboards, and automate forecasting and capacity models to improve scalability, repeatability, and timeliness.
• Use SQL and Python to extract, transform, and analyze large-scale operational datasets to monitor forecast accuracy, capacity gaps, utilization, and operational risk.
• Present forecast assumptions, methodologies, risks, trade-offs, and recommendations in clear, executive-ready formats and act as a trusted advisor to senior leadership and lead demand/capacity planning discussions in cross-functional forums.
• Align cross-functional stakeholders (Delivery, Product, Finance, HR, and others) to embed planning outputs into execution and operational decision-making.
• Identify and implement process improvements, automation, and best practices in the demand and capacity planning area to optimize cost while maintaining or improving customer experience and service-level outcomes.
• Lead, mentor, and develop planning analysts in quantitative methods, statistical rigor, and coding best practices.
• Review and approve forecasting and capacity models for accuracy, scalability, and business relevance.
• Set clear goals, high performance expectations, and career development paths for the team.
• Foster a culture of data-driven decision-making, accountability, and continuous improvement.
Requirements:
• 12+ years of experience in demand forecasting, capacity planning, workforce analytics, or applied analytics.
• 5+ years of people management experience.
• Bachelor’s degree in Mathematics, Statistics, Operations Research, Engineering, Economics, Data Science, or a related quantitative field.
• Strong foundation in probability, statistics, and optimization.
• Hands-on experience building and validating forecasting models (time series analysis, exponential smoothing, ARIMA, regression, hypothesis testing) and capacity models (Erlang, queueing theory, service-level and utilization modeling).
• Strong understanding of contact center metrics (AHT, ASA, service level, shrinkage, occupancy); experience supporting large-scale, multi-site, or global contact center environments preferred.
• Advanced analytical skills with strong proficiency in Excel, Google Sheets, SQL, Python and data visualization tools such as Tableau.
• Experience with WFM tools (e.g., NICE, Verint, Aspect) or planning platforms (e.g., Anaplan) preferred.
• Strong business acumen with the ability to balance cost efficiency and customer experience outcomes.
• Excellent communication, executive presentation, and stakeholder influence skills; ability to explain complex analytical concepts to non-technical audiences.
• Comfortable operating in fast-paced, ambiguous, and highly dynamic environments.
Benefits:
• This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.