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Data Scientist (Sales Operations)

AMD· Engineering
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Hybrid (Austin, TX)$112k - $168kFull-timePosted 2mo ago

About the role

Data Scientist to lead advanced analytics, predictive modeling, and generative AI initiatives for AMD's Sales Operations, collaborating cross-functionally to optimize revenue, improve operations, and automate tasks through data-driven solutions.

Responsibilities

  • Predictive Modeling & Machine Learning: Develop and deploy predictive models using ML algorithms (e.g., XGBoost, Random Forest) to address business challenges such as customer segmentation and revenue forecast; Build end-to-end ML pipelines from data ingestion to model deployment, ensuring scalability and reliability.
  • Time-Series Forecasting: Create robust time-series forecasting models for revenue, demand, and operational metrics; Partner with finance, sales, and operations teams to integrate forecasts into strategic planning and decision-making processes.
  • Generative AI & Advanced Analytics: Design and implement generative AI solutions (e.g., LLMs, GANs) for business applications such as information retrieval, workflow automation, and AI-driven decision systems.
  • Data Pipeline & Infrastructure: Collaborate with data engineering teams to design and maintain scalable data pipelines using tools like Airflow, KNIME, or custom shell scripting; Leverage big data frameworks (Snowflake, Hadoop, Spark) for efficient data processing and storage.
  • Exploratory Data Analysis & Visualization: Perform EDA to uncover patterns from structured and unstructured data; Develop visualizations using Plotly, Matplotlib, Seaborn to communicate findings.
  • Collaboration & Impact Measurement: Work with business leaders, data engineers, and BI teams to align on business needs and deliver impactful solutions; Monitor model performance post-deployment and iterate on models.
  • Continuous Learning & Innovation: Stay updated on emerging technologies in AI/ML and generative models; Experiment with new tools to enhance team capabilities and drive innovation.

Qualifications

  • Bachelor’s degree (Master’s preferred) in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field.
  • Technical Skills: Proficiency in Python, SQL, and other programming languages; strong understanding of ML algorithms and statistical techniques; hands-on experience with ML libraries (Scikit-learn, TensorFlow, PyTorch) and generative AI frameworks; familiarity with time-series forecasting methods and tools; experience with big data technologies (Snowflake, Hadoop, Spark); basic UNIX shell scripting (Bash, Zsh).
  • Experience: Minimum of 3+ years of experience in data science or related fields; demonstrated ability to deliver end-to-end ML projects; experience with Git/GitHub.
  • Business Acumen: Ability to translate technical insights into actionable business strategies; strong communication skills for cross-functional collaboration.

Skills

Required:PythonSQLMachine LearningTime-Series ForecastingCommunication
Nice to have:Generative AIBig Data TechnologiesData VisualizationUnix Shell

Benefits

  • Benefits offered are described: AMD benefits at a glance (link in posting)
Last updated Oct 22, 2026. Interested? Apply on the company site.
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About AMD

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AMD delivers leadership high-performance and adaptive computing solutions to advance data center AI, AI PCs, intelligent edge devices, gaming, & beyond.

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