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Open nowPosted today

Manager, Pricing Strategy & Analytics

Revelyst43 open roles

Pay
$130,000 – $140,000 a year
Where
Irvine, CA
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Your applicationOpen nowManager, Pricing Strategy & AnalyticsRevelyst · Irvine, CA

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The clock on this job

Early applications get read.

13.3% of postings close within 7 days. Measured by our own scanner across the market. Revelyst postings stay open a median of 31 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.6%3 days
  3. 13.3%7 days
  4. 21.3%14 days
  5. 35.7%30 days
  6. 59.1%60 days
This job: posted today

Revelyst median: 31 days open

The posting

Job Description

As the Manager, Pricing Strategy & Analytics, you will run the platform's EBITDA-first pricing engine: the seasonal list price process that classifies every SKU on elasticity and margin, the sales program and gross to net analytics that sit behind it, and the Power BI analytics landscape that tracks price, volume and mix from sell in through retail sell out. The strongest candidates are as comfortable writing DAX and SQL against a data lake as they are presenting a price recommendation that brand leadership can approve.

This position reports to the Senior Director, Pricing Strategy and is based in Irvine, CA.

As the Pricing Strategy & Analytics Manager, you will have an opportunity to:

Own the pricing engine:

  • Seasonal list price process: Run the list price cycle for each seasonal line plan: classify every SKU on elasticity and margin, apply price ladders, tiering, segmentation and Good/Better/Best architecture, document the price, volume and margin tradeoffs, and own the scenario model behind each recommendation. Prepare the recommendations that brand leadership reviews and approves ahead of sell in, and keep the process repeatable and on the go to market calendar.
  • Sales programs and gross to net: 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 that team maintains, with EBITDA optimization the objective.
  • Pricing return tracking: Track list price, program and promotional actions through the P&L after they ship, confirm that realized price, volume and margin land where the business case promised, and surface risks and opportunities against the long range plan.
  • Global pricing partnership: Partner with international and regional commercial teams so pricing decisions stay consistent across markets, and bring the relevant cost and currency considerations into those conversations.

Build the analytics landscape:

  • Power BI for revenue growth management: Build and operate the revenue growth management analytics landscape in Power BI: price realization forecasting and tracking, price strategy tracking, price, volume and mix decomposition by brand and category, the pricing readout in the monthly business review and the recurring executive readouts. Own the 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.
  • AI accelerated development: Use AI tooling such as Claude and Microsoft Copilot (DAX and measure generation, semantic model assistance) as the default way of building, help deliver AI assisted capabilities inside the dashboards such as scenario modeling and automated commentary, and replace manual templates with governed data and reusable AI workflows.
  • Elasticity and consumer response: Estimate price elasticity by category and channel from retail sell out data, using designs that hold up to scrutiny, and translate the results into the elasticity tiers that drive SKU classification and price gap analysis.
  • Channel analytics: Supply the pricing view of sell in versus sell out, including syndicated category and share tracking, retailer inventory and weeks of supply, built on demand planning's forecasts so channel inventory exposure is measured consistently by account.

Partner with the business:

  • Revenue and gross margin partnering: Partner with brand, channel and sales leaders across North America on the pricing assumptions in the revenue plan (units, average selling price and gross to net), and supply the price, mix and discount drivers to FP&A's gross margin bridges and profitability views.
  • Pricing decisions on existing and new products: Support pricing change requests from sales and new product pricing in the stage gate process with margin, volume and competitive analysis.

Key account pricing reviews:

  • Provide the elasticity, price gap and scenario analytics that key account managers use in retailer pricing and business reviews, and prepare retailer facing versions of the analysis suited to an external audience.

Governance and rigor:

  • Contribute to the pricing playbook and its regular refresh, prepare materials for the pricing governance forum, and hold every deliverable to one standard: numbers tie to source, units and denominators are checked, and measured figures are separated from assumptions.

You have:

  • 5+ years of progressive experience in pricing or revenue growth management, ideally in consumer products sold through wholesale, mass and ecommerce channels.
  • Demonstrated ownership of a pricing process end to end: list price setting, price architecture (ladders, tiering, Good/Better/Best), program or promotion effectiveness, and gross to net.
  • Applied experience estimating price elasticity from point of sale or transaction data, and the judgment to know when a design supports a causal claim and when it does not.
  • Power BI at the semantic model level (DAX measures, star schema design, performance tuning) and SQL.
  • Strong gross margin analytics: 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: concise commentary that leads with the answer, separates what was measured from what was assumed, and moves sales, brand and IT partners without direct authority.
  • Bachelor's degree in a quantitative field or equivalent experience.

You might have:

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

#LI-KK1

Pay Range:

Annual Salary: $130,000.00 - $140,000.00

The actual annual salary offered to a candidate will be based on variables including experience, geographic location, education, and skills/achievements, and will be mutually agreed upon at the time of offer.

We offer a highly competitive salary, comprehensive benefits including: medical and dental, vision, disability and life insurance, 401K, PTO, paid holidays, gear discounts and the ability to add value to an exciting mission!

Our Postings are not intended for distribution to or use in any jurisdiction, country or territory where such distribution or use would violate local law or would subject us to any regulations in another jurisdiction, country or territory. We reserve the right to limit our Postings in any jurisdiction, country or territory.

Equal Opportunity Employer Protected Veteran/Disabled

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