Haleon

Haleon

Consumption Forecasting & Analytics Analyst - Pain

USA - New Jersey - Warren

Sponsorship not specified$122k-$168kDetected 5 days ago
Data VisualizationStatisticsForecastingExcelCommunicationProblem SolvingVariance AnalysisDemand Planning

About the role

  • We're a purpose-driven, world-class consumer company putting everyday health in the hands of millions.
  • In just three years since our launch, we've grown, evolved and are now entering an exciting new chapter - one filled with bold ambitions and enormous opportunity.
  • What sets us apart is our unique blend of deep human understanding and trusted science.

Responsibilities

  • Develop and maintain data-driven consumption forecasts using retail sales (POS) data, advanced analytics (e.g. Marketing Mix), illness incidence, macro trends and other key data sources
  • Translate data into business insights and recommendations that help address strategic questions and support sales growth and share gains.
  • Support monthly business planning cycles by delivering forecast updates, variance analysis, and risk/opportunity insights while partnering cross-functionally with Marketing, Demand Planning, Sales, and Finance teams.
  • Develop and maintain dashboards and reporting tools to monitor business performance and forecast accuracy
  • This information ensures we meet certain regulatory and reporting obligations and supports the development, refinement, and execution of our inclusion and belonging programmes that are open to all Haleon employees.

Requirements

  • Advanced Excel skills required
  • If you are not sure whether the email you received is from Haleon, please get in touch.

Nice to have

  • If you have the following characteristics, it would be a plus:
  • Job Posting End Date
  • Equal Opportunities
  • Haleon are committed to mobilising our purpose in a way that represents the diverse consumers and communities who rely on our brands every day.
  • It's important to us that Haleon is a place where all our employees feel they truly belong.
  • The personal information you provide will be kept confidential, used only for legitimate business purposes, and will never be used in making any employment decisions, including hiring decisions.
  • This capture of applicable transfers of value is necessary to ensure Haleon's compliance to all federal and state US Transparency requirements.
  • Accommodation Requests

Skills

  • Bachelor's degree in Business Analytics, Economics, Business, Statistics, or related field
  • 3+ years of experience in analytics, forecasting, or consulting, preferably in the CPG industry
  • Strong foundation in statistical analysis and regression modeling
  • Experience with forecasting tools and syndicated data sources (e.g., Circana, Nielsen)
  • Experience working with incidence data (e.g. IQVIA data) preferred
  • Advanced Excel skills required; experience with Power BI is a plus
  • Strong problem-solving skills with the ability to translate data into business insights
  • Excellent communication skills; able to present findings clearly to non-technical audiences

Compensation

  • The salary range for this role is $ 121,952 - $ 167,684 USD annually + bonus

Benefits

  • Haleon offers a robust Total Reward package that consists of competitive pay and a comprehensive benefits program.
  • This includes a generous 401(k) plan, tuition reimbursement and time off programs including 6 months paid parental leave.
  • On day one, you are eligible for benefits, including our healthcare programs where the company pays for the majority of your medical coverage for you and your family.
  • We also offer the opportunity to receive a discretionary bonus based on the achievement of key business performance and other incentive/recognition programs as part of the offering.

Equal opportunity

  • Job Accommodation Request'
  • Your Name and contact information
  • Requisition ID and Job Title you are interested in
  • Location of Requisition (city/state or province/country)

This listing is sourced directly from Haleon's careers page and normalized into a canonical job model.