Manager, Pricing Strategy & Analytics

Revelyst Outdoor•Irvine, CA

2d•$130,000 - $140,000

About The Position

The Manager, Pricing Strategy & Analytics owns the company’s EBITDA-first pricing engine, including seasonal list pricing, sales program and gross-to-net analytics, and Power BI analytics that track price, volume, and mix from sell-in through retail sell-out. The role develops and documents pricing recommendations for brand leadership, measures pricing outcomes against business cases, and partners with finance, commercial, brand, sales, and IT teams to support profitable decisions. The manager builds and operates the revenue growth management analytics landscape in Power BI, including semantic models and DAX measures within IT governance, using the Azure data lake in partnership with IT. The position also estimates price elasticity from retail sell-out data, analyzes channel inventory exposure, and uses generative AI tools to accelerate analytics and reporting while validating their outputs. The role supports revenue and gross margin planning, pricing changes for existing products and new product stage gates, and key account pricing reviews. It contributes to pricing governance and the pricing playbook, ensuring deliverables are traceable to source data and clearly distinguish measured results from assumptions. The position reports to the Senior Director, Pricing Strategy and is based in Irvine, California.

Requirements

At least 5 years of progressive experience in pricing or revenue growth management.
Demonstrated end-to-end ownership of a pricing process, including list price setting, price architecture, program or promotion effectiveness, and gross-to-net.
Applied experience estimating price elasticity from point-of-sale or transaction data, with judgment about whether an analytical design supports a causal claim.
Power BI experience at the semantic model level, including DAX measures, star schema design, and performance tuning.
SQL experience.
Strong gross margin analytics experience, including standard costing, price and mix, discounts and allowances, and landed cost drivers.
Experience using generative AI assistants to accelerate analysis, coding, and reporting, with discipline in verifying their output.
Executive communication and influence skills, including concise commentary that distinguishes measured results from assumptions and the ability to influence sales, brand, and IT partners without direct authority.
Bachelor’s degree in a quantitative field or equivalent experience.

Nice To Haves

Pricing or revenue growth management experience with consumer products sold through wholesale, mass, and ecommerce channels.
Python for data preparation and modeling.
Working knowledge of modern data platforms, including Azure data lake or lakehouse architectures.
Working knowledge of ERP and planning data, such as SAP, Oracle, or Planful.
Familiarity with syndicated retail data and retailer sell-out feeds.
MBA or a master’s degree in a quantitative discipline.

Responsibilities

Run the seasonal list price cycle for each seasonal line plan, classifying every SKU by elasticity and margin and applying price ladders, tiering, segmentation, and Good/Better/Best architecture.
Document price, volume, and margin tradeoffs; own the scenario model behind pricing recommendations; prepare recommendations for brand leadership; and keep the process repeatable and aligned with the go-to-market calendar.
Model sales program scenarios by brand and channel and quantify gross-to-net and volume impacts in partnership with the finance owner of sales programs.
Track list price, sales program, and promotional actions through the P&L after launch, check realized price, volume, and margin against business cases, and surface risks and opportunities against the long-range plan.
Partner with international and regional commercial teams on consistent pricing decisions across markets, incorporating relevant cost and currency considerations.
Build and operate the Power BI revenue growth management analytics landscape, including price realization forecasting and tracking, price strategy tracking, price-volume-mix decomposition, monthly business review pricing readouts, 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 tools such as Claude and Microsoft Copilot to accelerate development; help deliver 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 defensible analytical designs, and translate results into elasticity tiers for SKU classification and price gap analysis.
Provide channel analytics on sell-in versus sell-out, syndicated category and share tracking, retailer inventory, and weeks of supply, using demand planning forecasts to measure account inventory exposure consistently.
Partner with brand, channel, and sales leaders across North America on pricing assumptions in revenue plans, including units, average selling price, and gross-to-net.
Supply price, mix, and discount drivers for FP&A gross margin bridges and profitability views.
Support pricing change requests from sales and new product pricing through the stage-gate process with margin, volume, and competitive analysis.
Provide elasticity, price gap, and scenario analytics for key account retailer pricing and business reviews, and prepare versions suitable for external audiences.
Contribute to the pricing playbook and its regular refresh, prepare materials for the pricing governance forum, and ensure deliverables tie to source data, use checked units and denominators, and separate measured figures from assumptions.