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Revelyst

Manager – Pricing Strategy & Analytics

Business OperationsUpdated on Nov 15
Full-timeIrvine, CA, USA$130k - $140k /yr

About the Job

Requirements

  • At least 5 years of progressive experience in pricing or revenue growth management, ideally in consumer products sold through wholesale, mass, and ecommerce channels.
  • Demonstrated end-to-end ownership of a pricing process, including list price setting, price architecture such as ladders, tiering, and Good/Better/Best, program or promotion effectiveness, and gross to net.
  • Applied experience estimating price elasticity from point-of-sale or transaction data, with the judgment to distinguish designs that support causal claims from those that do not.
  • Power BI experience at the semantic model level, including DAX measures, star schema design, and performance tuning, and SQL experience.
  • Strong gross margin analytics skills covering standard costing, price and mix, discounts and allowances, and landed cost drivers.
  • Experience using generative AI assistants to accelerate analysis, code, and reporting, with the discipline to verify their output.
  • Ability to communicate concisely to executives, distinguish measured results from assumptions, and influence sales, brand, and IT partners without direct authority.
  • A bachelor's degree in a quantitative field or equivalent experience.

Responsibilities

  • Run the seasonal list price cycle for each seasonal line plan by classifying every SKU on elasticity and margin; applying price ladders, tiering, segmentation, and Good/Better/Best architecture; documenting price, volume, and margin tradeoffs; and owning the scenario model behind each recommendation.
  • Prepare list price recommendations for brand leadership review and approval ahead of sell-in, and keep the process repeatable and aligned with the go-to-market calendar.
  • Model sales program scenarios by brand and channel and quantify their gross-to-net and volume impact, working with the finance owner of sales programs and the discount reporting maintained by that team, with EBITDA optimization as the objective.
  • Track list price, program, and promotional actions through the P&L after they ship; confirm realized price, volume, and margin against the business case; and surface risks and opportunities against the long-range plan.
  • Partner with international and regional commercial teams to maintain pricing consistency across markets and incorporate relevant cost and currency considerations.
  • Build and operate the revenue growth management analytics landscape in Power BI, including price realization forecasting and tracking, price strategy tracking, price-volume-mix decomposition by brand and category, the pricing readout in the monthly business review, and recurring executive readouts.
  • Own pricing semantic models and DAX measures within IT's Power BI governance, with a named backup, built on the Azure data lake in partnership with IT.
  • Use AI tooling such as Claude and Microsoft Copilot for DAX and measure generation and semantic model assistance; help deliver AI-assisted dashboard capabilities such as scenario modeling and automated commentary; and replace manual templates with governed data and reusable AI workflows.
  • Estimate price elasticity by category and channel from retail sell-out data using designs that hold up to scrutiny, and translate the results into elasticity tiers that drive SKU classification and price gap analysis.
  • Supply channel analytics comparing sell-in and sell-out, including syndicated category and share tracking, retailer inventory, and weeks of supply, built on demand planning forecasts to measure channel inventory exposure consistently by account.
  • Partner with brand, channel, and sales leaders across North America on pricing assumptions in the revenue plan, including units, average selling price, and gross to net; provide price, mix, and discount drivers for FP&A gross margin bridges and profitability views.
  • Support pricing change requests from sales and new product pricing in the stage-gate process with margin, volume, and competitive analysis.
  • Provide elasticity, price gap, and scenario analytics for key account managers' retailer pricing and business reviews, and prepare retailer-facing versions of the analysis for external audiences.
  • Contribute to the pricing playbook and its regular refresh, prepare materials for the pricing governance forum, and ensure deliverables tie numbers to source, check units and denominators, and separate measured figures from assumptions.

Desired Qualifications

  • Python for data preparation and modeling.
  • Working knowledge of modern data platforms, including Azure data lake or lakehouse architectures, and ERP and planning data such as SAP, Oracle, and Planful.
  • Familiarity with syndicated retail data and retailer sell-out feeds.
  • An MBA or master's degree in a quantitative discipline.

About the Company

Company size
1,001-5,000
Company stage
Acquired
Total funding
Not listed
Headquarters
Anoka, MN
Founded
2023

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