Rambus

Introduction

At Rambus, I served as a Contract Product Manager, where I worked on aligning next-generation chipset/IP product strategy with market demand. My projects focused on roadmap prioritization, forecasting accuracy, and cross-functional execution. I combined technical modeling with market research to improve forecast reliability and support product delivery across the Rambus ecosystem.


 

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Steps

Approach Process

Evaluated 25+ chipsets/IP products to compare performance and identify roadmap gaps

Built Hex-driven SQL model to measure forecast accuracy and surface risk

Analyzed 15,000+ datapoints from 4 firms to test assumptions across 40+ forecasts

Ran A/B tests with engineering, tracked progress in Jira, cut forecast errors by 15%

Project Process

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Data Analysis through SQL + Python

Standardized 15,000+ datapoints using SQL automation in Hex, normalizing variables such as quarter, metric, and prediction vs. actual. This structured dataset enabled reliable evaluation of 40+ demand forecasts and laid the foundation for accuracy testing

The details of awards from various

Applied Python analytics to evaluate forecast accuracy, visualizing error trends across 40+ models. The analysis surfaced high-risk assumptions and reduced forecast errors by 15%, informing roadmap updates and GTM strategy

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Impact

Data Points Analyzed
0 K+
Cut in Forecast Errors
0 %
Forecasts Modeled
0 +