This role pays less than
91%
of similar roles. Most pay
$126,800–$199,575
— the shaded band above.
At the midpoint, this role pays about
$123k
versus about
$163k
for comparable roles.
Based on 240 similar postings.
Employer
About Amd
AMD (Advanced Micro Devices) is a semiconductor company that develops high-performance processors, graphics cards, and adaptive computing solutions for gaming, data centers, and embedded markets. Industry: Semiconductors
Amd currently has
367 open roles
on FindRole.
Listed pay typically runs
$166,400–$249,600
across 367 roles with salary data.
Data Scientist - Pricing & Profitability joins the AECG Pricing & Profitability Optimization team to transform data into pricing decisions that protect and grow gross margin across the adaptive and embedded portfolio. This role involves building AI/LLM tooling, machine-learning models, analytics platforms, and automated workflows to replace manual processes with scalable solutions. The successful candidate will develop predictive models for pricing and margin forecasting, engineer reliable data pipelines in Snowflake, and create tools that automate reporting and decision support. Key technical requirements include proficiency in Python for production-quality code, SQL for querying structured data, and experience with generative AI technologies like RAG and agentic workflows. The role requires translating complex technical insights into explainable stories for business stakeholders while managing a cross-functional platform consolidating quote, cost, and point-of-sale data to provide a single source of truth.
What does a Data Scientist earn in California?
Median $208978 from 66 postings across 27 companies.
Design, develop, and maintain internal AI/LLM-based tools to automate pricing analysis and business workflows.
Prototype and evaluate agentic workflows and RAG techniques to replace manual pricing processes with automated systems.
Develop and refine machine learning models for pricing and margin forecasting using large, complex datasets.
Build and manage reliable data pipelines by querying and modeling structured data in Snowflake.
Automate the generation of recurring reports, alerts, and executive decision-support materials from underlying data.
Deploy, monitor, and recalibrate production models to ensure ongoing accuracy and performance.
Maintain a cross-functional data platform that consolidates quote, cost, and point-of-sale data into a single source of truth.
Translate complex technical insights and model outputs into actionable stories for executive leadership.
What we're looking for
Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Business Analytics, Engineering, Finance, or a related quantitative field.
Experience in data science and analytics, preferably supporting pricing, finance, sales operations, or commercial analytics functions.
Hands-on experience with LLMs and generative AI, including prompt engineering, RAG, and agent frameworks.
Proficiency in Python for data work, automation, and writing production-quality code.
Proficiency in SQL and experience working with Snowflake or other cloud data platforms.
Experience building, testing, and deploying machine learning models for pricing, forecasting, or predictive analytics.
Ability to translate complex technical models into explainable insights and stories for executive audiences.
Familiarity with pricing systems, CPQ, quote-to-cash, or Deal Desk processes is preferred.
Python
R
SQL
Machine Learning
Data Visualization
Inferential Statistics
Data Analytics
Data Cleansing
System Integration
Web Applications
Item Response Theory
Factor Analysis
Data Governance
Research Design