Data Scientist- Install Automation

Applied Materials
Austin
Workplace: OnsiteFull timeUSD 78,500 - 108,000 annuallyFunction: Data Science & Machine LearningExperience: 3+ yearsEducation: mastersSkills: ["Analytical","Problem-solving","Communication"]

Develop and deploy AI, machine learning, and analytics solutions to automate installation workflows, including install automation, auto sequencing, and smart sequencing. Build predictive and optimization models to improve efficiency, resource utilization, workflow execution, and cycle-time performance. Analyze engineering and operational data, design data pipelines and model monitoring, and apply generative AI for automation and decision-making. Partner with engineering and manufacturing teams and deliver dashboards and KPI frameworks to measure impact.

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FursaFursa
Applied Materials
Applied Materials
2 months ago

Data Scientist- Install Automation

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Source: Company careers pageValidated by: Fursa AI
Last checked: 20 hours agoStatus: Live

Job Summary

Develop and deploy AI, machine learning, and analytics solutions to automate installation workflows, including install automation, auto sequencing, and smart sequencing. Build predictive and optimization models to improve efficiency, resource utilization, workflow execution, and cycle-time performance. Analyze engineering and operational data, design data pipelines and model monitoring, and apply generative AI for automation and decision-making. Partner with engineering and manufacturing teams and deliver dashboards and KPI frameworks to measure impact.
Location: Austin
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Develop and deploy AI, machine learning, and analytics solutions for install automation, auto sequencing, smart sequencing, and task automation initiatives.
  • •Build predictive and optimization models to improve installation efficiency, resource utilization, workflow execution, and cycle-time performance.
  • •Analyze engineering, installation, service, and operational data to identify patterns, predict outcomes, and drive automation decisions.
  • •Design and implement data pipelines and end-to-end ML processes including feature engineering, model training, validation, deployment, and monitoring.
  • •Apply machine learning, optimization techniques, and Generative AI to automate engineering workflows, documentation, and decision-making.
Travel: Low travel

Pay and Benefits

Salary: USD 78,500 - 108,000 annually
Perks:Travel Allowance

Key Requirements

  • •Bachelor's or Master's degree in Data Science, Computer Science, Engineering, Statistics, Artificial Intelligence, or related field.
  • •3+ years of experience in Data Science, Machine Learning, AI, Advanced Analytics, or Process Automation.
  • •Strong proficiency in Python and machine learning frameworks such as Scikit-Learn, TensorFlow, PyTorch, or equivalent.
  • •Experience building predictive models, optimization algorithms, recommendation systems, or workflow automation solutions.
  • •Knowledge of supervised/unsupervised learning, deep learning, Generative AI, and statistical modeling.
Experience:3+ years
Education:Master's in Data Science, Computer Science, Engineering, Statistics, Artificial Intelligence, or related field
Skills:AnalyticalProblem-solvingCommunication
Tech Stack:PythonScikit-LearnTensorFlowPyTorchGenerative AIMachine learningAnalyticsData pipelinesFeature engineeringModel trainingModel validationDeploymentMonitoringDashboardsKPI frameworks

Company Brief

Applied Materials
Provides semiconductor manufacturing equipment, services, and software used to build advanced chips and display technologies. Its tools support materials engineering, deposition, etching, inspection, and process control for major electronics manufacturers worldwide.
Industry: Industrial Machinery
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: 1967
Glassdoor
Glassdoor: 3.9
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