Data Scientist (Sales Operations)

AMD
Austin
Workplace: HybridFull timeFunction: Revenue Operations (RevOps)Experience: 3+ yearsEducation: bachelorsSkills: ["Communication","Collaboration","Business acumen","Innovation","Continuous learning"]

Lead advanced analytics and machine learning initiatives for the Sales Operations org, building predictive and time-series forecasting models to drive revenue and operational decisions. Design and deploy generative AI solutions for practical business use cases, partner across finance and sales to operationalize insights, and collaborate with data engineering on scalable pipelines using modern big data tools and ML infrastructure.

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FursaFursa
AMD
AMD
1 day ago

Data Scientist (Sales Operations)

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 7 hours agoStatus: Live
Reposted: similar role first listed 5 months ago

Job Summary

Lead advanced analytics and machine learning initiatives for the Sales Operations org, building predictive and time-series forecasting models to drive revenue and operational decisions. Design and deploy generative AI solutions for practical business use cases, partner across finance and sales to operationalize insights, and collaborate with data engineering on scalable pipelines using modern big data tools and ML infrastructure.
Location: Austin
Workplace: Hybrid
Employment Type: Full time
Job Function: Revenue Operations (RevOps)
Seniority: Mid level

Key Responsibilities

  • •Develop and deploy predictive machine learning models (e.g., XGBoost, Random Forest) for business use cases like segmentation and revenue forecasting.
  • •Build end-to-end ML pipelines from data ingestion through model deployment with scalability and reliability in mind.
  • •Create time-series forecasting models for revenue, demand, and operational metrics (e.g., ARIMA, Prophet, Bayesian and hybrid approaches).
  • •Design and implement generative AI solutions for business applications such as information retrieval, workflow automation, and AI-driven decision systems.
  • •Collaborate with data engineering and business teams to design scalable data pipelines and visualize/explain insights, while monitoring model performance post-deployment.

Key Requirements

  • •Bachelor’s degree (Master’s preferred) in Data Science, Computer Science, Statistics, Applied Mathematics, or related fields.
  • •Proficiency in Python and SQL, plus strong statistical and machine learning fundamentals.
  • •Hands-on experience with ML libraries (Scikit-learn, TensorFlow, PyTorch) and generative AI frameworks.
  • •Experience building time-series forecasting models and familiarity with tools/methods such as ARIMA and Prophet.
  • •Minimum 3+ years delivering end-to-end data science/ML projects, including experience with version control (Git, GitHub).
Experience:3+ yearsSales operationsRevenue forecastingGenerative AIPredictive modeling
Education:Bachelor's
Skills:CommunicationCollaborationBusiness acumenInnovationContinuous learning
Languages:English
Tech Stack:PythonSQLXGBoostRandom ForestARIMAProphetAirflowKNIMESnowflakeHadoopSparkScikit-learnTensorFlowPyTorchLLMsGANsPlotlyMatplotlibSeabornGit

Eligibility

Work Authorization:Authorization required. Sponsorship not provided.

Company Brief

AMD
Designs and produces semiconductor products including CPUs, GPUs, and adaptive SoCs for consumer, enterprise, and embedded markets, competing across PCs, data centers, and gaming industries.
Industry: Electronics Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1969
Glassdoor
Glassdoor: 3.9
WebsiteLinkedIn