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Location
Remote (Philippines)
Seniority
Senior · 5+ years exp

Confirmed on the employer's own hiring board on Nov 3, 2026. First seen by Alion on Nov 2, 2026. Dayforce scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Dayforce is a Toronto software company that provides cloud human capital management to large employers. Its platform runs payroll, workforce management and talent processes on a single continuous calculation engine rather than batch cycles. The company is listed in New York and Toronto and was previously named Ceridian.

About the Opportunity

We are seeking an experienced Senior Workforce Analyst - Forecasting, WFM Analytics & AI to help advance our forecasting and workforce planning capabilities. This role is designed for a seasoned forecasting professional who can independently lead complex forecasting and workforce analytics while modernizing how forecasts are developed, monitored, analyzed, and communicated. The successful candidate will combine strong forecasting and WFM expertise, advanced Power BI capabilities, structured problem solving, automation, and practical application of AI to answer the questions that matter most: What changed? Why did it change? Is it temporary or structural? What happens next? What is the workforce impact? What action should we take? You will partner with Operations, Workforce Management, Finance, Data/Technology teams, and senior leaders to translate complex operational data into actionable workforce decisions 

Location: Work is what you do, not where you go. For this role, we are open to remote work and can hire anywhere in the Philippines.

What You’ll Get to Do:

Lead the development and continuous improvement of workforce forecasting, capacity planning, and workforce analytics methodologies across complex operational workstreams.

Develop integrated, driver-based forecasts across voice, chat, cases/tickets, and asynchronous or backlog workloads, accounting for channel-specific demand patterns, productivity, concurrency, service targets, and shared capacity.

Translate different workload types and productivity measures into a common capacity framework that provides clear views of required FTE, available capacity, over/under position, service risk, and resource-rebalancing opportunities.

Perform advanced variance, trend, and root-cause analysis to distinguish normal variation and seasonality from emerging or structural changes in demand, productivity, backlog, staffing, and service performance.

Build scenario and sensitivity models to quantify the workforce impact of changes in demand, productivity, staffing, shrinkage, attrition, automation, service expectations, and other business assumptions.

Design and enhance Power BI dashboards, data models, DAX measures, KPIs, and executive reporting that connect workforce drivers with operational and customer outcomes.

Develop automated and exception-based monitoring to identify meaningful changes in demand, productivity, capacity, backlog, SLA, AHT, shrinkage, forecast performance, and other workforce drivers.

Apply AI and automation to accelerate forecast analysis, anomaly detection, scenario development, data validation, insight generation, and recurring analytical workflows.

Evaluate AI-generated analysis using statistical validation, operational context, business knowledge, human judgment, and appropriate governance to ensure recommendations are reliable and actionable.

Partner with Operations, WFM, Finance, Data and Technology teams, and senior leaders to challenge assumptions, incorporate forward-looking business intelligence, and influence workforce and capacity decisions.

Identify opportunities for capacity optimization, cross-skilling, resource allocation, process improvement, and automation across teams and work types.

Help establish forecasting and WFM standards, improve analytical practices, and mentor analysts in forecasting, workforce analytics, problem solving, and insight development.

Skills and Experience We Value:

5–7+ years of progressive experience in workforce forecasting, capacity planning, workforce management, operational forecasting, or advanced workforce analytics within a complex operational environment.

Demonstrated expertise building driver-based workforce forecasts and translating workload, productivity, and service assumptions into staffing/FTE requirements, capacity gaps, risks, and operational recommendations.

Strong multi-channel forecasting experience across voice, chat, cases/tickets, and asynchronous or backlog work, including consolidating different demand and productivity measures into workforce requirements.

Deep knowledge of WFM principles and practices, including demand forecasting, workload and capacity planning, staffing requirements, scheduling, shrinkage, occupancy, adherence, service level, AHT, Erlang methodology, intraday management, and forecast accuracy and bias.

Experience modelling shared and cross-skilled resources across channels or work types and evaluating capacity allocation, work prioritization, and resource-rebalancing opportunities.

Advanced, hands-on Power BI experience, including dashboard development, data modelling, DAX, measures, KPIs, visualization, and executive-level reporting.

Demonstrated practical experience using AI and automation within forecasting, workforce planning, or advanced analytics workflows, such as anomaly and trend detection, scenario analysis, data validation, insight generation, or process automation.

Ability to combine AI-generated analysis with statistical validation, operational context, and human judgment to produce credible workforce recommendations.

Strong analytical and problem-solving capability, with the ability to connect forecast accuracy, staffing, scheduling, adherence, shrinkage, productivity, backlog, and service outcomes to identify root causes.

Experience applying statistical techniques such as control limits, correlation, regression, anomaly detection, or similar methods to distinguish normal variation from meaningful operational change.

Strong analytical storytelling and communication skills, with demonstrated ability to explain complex findings clearly and influence operational and senior leaders through evidence-based recommendations.

Bachelor’s degree in Business, Finance, Analytics, Mathematics, Statistics, Economics, Operations Research, Data Analytics, or a related discipline, or equivalent practical experience.

What Would Make You Really Stand Out:

Experience supporting complex contact center, case/backlog, SaaS, HCM, Managed Services, Customer Operations, Salesforce, or enterprise WFM environments.

Lean Six Sigma Green Belt certification or equivalent practical experience applying structured root-cause analysis and continuous-improvement methodologies.

Experience developing forecasting or workforce capabilities that move teams from manual reporting toward automated, exception-based, and proactive decision support.

Experience identifying and implementing opportunities for cross-skilling, capacity optimization, resource reallocation, or workforce automation.

Demonstrated ability to act as a trusted workforce advisor, moving beyond reporting numbers to explain what changed, why it changed, whether the change is temporary or structural, what is likely to happen next, and what action the business should take.

A forward-looking mindset and curiosity about how AI, automation, advanced analytics, and emerging technologies can improve workforce forecasting and decision-making.

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