Manager, Pricing Strategy & Analytics

Revelyst•Irvine, CA

10h•Onsite

About The Position

The Manager, Pricing Strategy & Analytics runs the company’s EBITDA-first pricing engine, including seasonal list pricing, sales program and gross-to-net analytics, and Power BI reporting that tracks price, volume, and mix from sell-in through retail sell-out. The role combines hands-on DAX and SQL development with the ability to present clear, decision-ready recommendations to brand leadership. It reports to the Senior Director, Pricing Strategy and is based in Irvine, California. The manager owns seasonal price-setting processes, including SKU elasticity and margin classification, price ladders, tiering, segmentation, Good/Better/Best architecture, scenario modeling, and documentation of price, volume, and margin tradeoffs. The role models sales program scenarios by brand and channel, tracks realized pricing and profitability against business cases, and works with regional and international teams on consistent pricing decisions that account for cost and currency considerations. The role builds and operates the revenue growth management analytics landscape in Power BI, including price realization forecasting and tracking, price strategy tracking, price-volume-mix analysis, and monthly and executive readouts. It owns pricing semantic models and DAX measures within IT’s Power BI governance, working with IT on Azure data lake foundations. It also uses AI tools to accelerate development and help deliver dashboard capabilities such as scenario modeling and automated commentary. The manager estimates elasticity from retail sell-out data, provides channel analytics on sell-in versus sell-out, syndicated category and share performance, retailer inventory, and weeks of supply, and partners with brand, channel, sales, finance, and FP&A on revenue planning and gross margin analysis. Additional work includes support for pricing changes and new product pricing, key account pricing reviews, retailer-facing analysis, pricing governance materials, and maintaining rigorous standards for source data, units, denominators, and separation of measured results from assumptions.

Requirements

At least 5 years of progressive experience in pricing or revenue growth management; consumer products sold through wholesale, mass, and ecommerce channels are preferred.
Demonstrated end-to-end ownership of a pricing process, including list price setting, price architecture, program or promotion effectiveness, and gross-to-net analysis.
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 skills.
Strong gross margin analytics, including 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.
Executive communication and influence skills, including concise answer-led commentary, distinction between measured and assumed information, and ability to influence sales, brand, and IT partners without direct authority.
Bachelor’s degree in a quantitative field or equivalent experience.

Nice To Haves

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 master’s degree in a quantitative discipline.

Responsibilities

Run the seasonal list price cycle for each line plan, classifying SKUs on elasticity and margin and applying price ladders, tiering, segmentation, and Good/Better/Best architecture.
Document price, volume, and margin tradeoffs and own the scenario models supporting pricing recommendations.
Prepare recommendations for brand leadership approval ahead of sell-in and keep the pricing 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 sales programs finance owner.
Track list price, sales program, and promotional actions through the P&L; assess 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 to support consistent pricing decisions across markets, incorporating relevant cost and currency considerations.
Build and operate Power BI revenue growth management analytics, including price realization forecasting and tracking, price strategy tracking, price-volume-mix analysis, monthly business review readouts, and recurring executive readouts.
Own pricing semantic models and DAX measures within IT’s Power BI governance, with a named backup, in partnership with IT and on the Azure data lake.
Use AI tools to accelerate analytics development and help deliver dashboard capabilities such as scenario modeling and automated commentary; replace manual templates with governed data and reusable AI workflows.
Estimate price elasticity by category and channel using retail sell-out data and translate results into elasticity tiers for SKU classification and price gap analysis.
Provide sell-in versus sell-out pricing analytics, including 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.
Provide price, mix, and discount drivers for FP&A gross margin bridges and profitability views.
Support sales pricing change requests 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 retailer pricing and business reviews, and prepare external-facing versions of the analysis.
Contribute to the pricing playbook and its regular refresh, prepare pricing governance forum materials, and ensure deliverables tie to source data, use checked units and denominators, and distinguish measured figures from assumptions.