below marketmost similar roles pay hereabove market
This role pays less than
52%
of similar roles. Most pay
$159,000–$214,225
— the blue band above.
At the midpoint, this role pays about
$180k
versus about
$187k
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
496 open roles
on FindRole.
Listed pay typically runs
$172,000–$258,000
across 496 roles with salary data.
The Sr. Data Analytics Manager will join the Marketing Analytics team to build and scale data science capabilities from the ground up. This role involves identifying high-impact analytics opportunities across the full marketing funnel, developing an operating model, and owning the data science roadmap. Key responsibilities include designing advanced analytical solutions such as lead scoring, attribution, marketing mix modeling, experimentation, forecasting, and propensity modeling. The successful candidate will partner with Marketing, Product, and Sales Operations to embed data-driven insights into decision-making and campaign optimization. Required skills include proficiency in Python, R, SQL, cloud data platforms, and machine learning frameworks. The role focuses on solving business problems related to demand generation, pipeline conversion, and marketing investment measurement within a complex marketing and sales data ecosystem.
Build and scale the marketing data science operating model, including frameworks, tools, processes, and governance.
Develop and own the marketing data science roadmap to prioritize high-impact analytics opportunities across the full marketing funnel.
Design and deliver advanced analytical solutions such as lead scoring, attribution, marketing mix modeling, and propensity modeling.
Measure and demonstrate business impact by establishing performance indicators and feedback loops for models and marketing investments.
Partner with Marketing, Product, and Sales Operations to embed analytics into planning and decision-making processes.
Collaborate with data engineering and technology teams to improve data quality, accessibility, and model deployment.
Translate complex analytical findings into clear business recommendations for technical, marketing, and executive audiences.
What we're looking for
Bachelor’s degree in Data Science, Statistics, Mathematics, Economics, Computer Science, Engineering, Marketing Analytics, or a related quantitative field.
Master’s degree or equivalent advanced experience (preferred).
Experience in data science, advanced analytics, marketing analytics, or a related discipline, including leading complex, cross-functional analytics initiatives (preferred).
Demonstrated success building or scaling a data science or advanced analytics capability, including defining the roadmap, operating model, and governance (preferred).
Hands-on knowledge of marketing mix modeling, multi-touch attribution, experimentation, forecasting, segmentation, propensity modeling, causal inference, and campaign optimization (preferred).
Proficiency with Python or R, SQL, cloud data platforms, machine learning frameworks, and visualization tools (preferred).
Experience partnering with data engineering, IT, and platform teams to improve data quality and operationalize models (preferred).
Proven ability to build trusted relationships with senior stakeholders and translate complex analytical findings into clear business recommendations (preferred).
Data Analytics
Statistical Modeling
Relational Database
Open Source Data Technologies
Predictive Analytics
Data Governance
Econometrics
Large Data Sets
SQL
Python
R
Tableau
PowerBI
Spark
Scala
Matplotlib
NoSQL
Oracle
Apache Mahout
Data Modeling
Data Quality Management
Data Governance
Data Profiling
Data Integration
KDD
Statistical Analysis
Data Analytics
Business Intelligence
SQL
Python
Tableau
PowerBI
NoSQL
Spark
Scala
R
Data Quality Management
Data Governance
Data Visualization
Distributed Data Storage
Data Science
Statistics
Automation