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Senior · 8+ years exp
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First seen by Alion on Nov 9, 2026. Applied Materials scores A on the Alion truth index.

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Applied Materials is the largest supplier of semiconductor manufacturing equipment in the world, founded in Santa Clara in 1967 and now shipping the deposition, etch, implantation, thermal processing and inspection systems used to build transistors and interconnects. Its tools sit at the heart of nearly every advanced logic and memory fab, and the company also supplies equipment for display panels and a services business that maintains the large installed base. Headquartered in Santa Clara and listed on Nasdaq, it invests heavily in materials engineering research aimed at extending device scaling beyond conventional lithography limits.

Job description:


As a Data Scientist, you will develop data-driven insights, predictive models, and optimization solutions that improve semiconductor manufacturing operations. You will work closely with customers, domain experts, and engineering teams to transform large-scale manufacturing and simulation data into actionable recommendations and intelligent decision-support capabilities.


The role combines statistical analysis, machine learning, optimization, simulation, and experimentation. You will contribute to both customer projects and internal innovation efforts while helping bridge the gap between business challenges and technical solutions.


Key Responsibilities:

  • Collect, process, and analyze manufacturing, simulation, and operational datasets.
  • Perform exploratory data analysis (EDA) to identify trends, bottlenecks, anomalies, and opportunities for improvement.
  • Develop statistical models and analytical frameworks to support operational decision making.
  • Translate complex analytical findings into clear business recommendations.
  • Design, develop, and validate predictive models for forecasting, classification, anomaly detection, and optimization use cases.
  • Apply operations research, statistical learning, and optimization techniques to solve manufacturing challenges.
  • Contribute to hybrid solutions that combine analytics, machine learning, and simulation technologies.
  • Design experiments and perform rigorous analysis to validate model effectiveness and business impact.
  • Work with simulation technologies, including discrete-event simulation (DES), to evaluate manufacturing scenarios and operational strategies.
  • Analyze simulation outputs and combine them with historical operational data.
  • Develop methodologies that improve planning, scheduling, resource utilization, and factory performance.
  • Work directly with customers, domain experts, and project teams to understand business requirements.
  • Present technical findings and recommendations to both technical and non-technical audiences.
  • Document datasets, methodologies, experiments, and analytical conclusions.
  • Contribute to customer workshops, solution design sessions, and project reviews.
  • Stay current with developments in data science, statistics, optimization, and applied machine learning.
  • Evaluate emerging methodologies and identify opportunities to improve customer outcomes.
  • Support research initiatives focused on manufacturing intelligence and decision-support technologies.


Required Skills:

  • Strong foundation in statistics, mathematics, and data analysis.
  • Experience developing predictive and analytical models.
  • Strong Python programming skills.
  • Hands-on experience with Pandas, Polars, NumPy, Scikit-learn, and related analytical tooling.
  • Experience with feature engineering, exploratory analysis, and model evaluation.
  • Understanding of optimization techniques, statistical experimentation, and hypothesis testing.
  • Strong problem-solving and analytical thinking skills.
  • Ability to communicate technical concepts to diverse stakeholders.


Preferred Skills:

  • Experience with discrete-event simulation or operations research.
  • Experience with manufacturing, scheduling, supply chain, or industrial systems.
  • Familiarity with machine learning deployment and MLOps concepts.
  • Experience working with high-dimensional or time-series datasets.
  • Knowledge of semiconductor manufacturing or advanced industrial environments.


About the Team:


You will be joining a highly experienced team of data scientists, AI engineers, software developers, and cloud architects, many with over a decade of experience delivering innovative solutions across multiple industries. Our work spans embedded software, renewable energy optimization, advanced scheduling systems, and AI-driven decision support platforms for multi-billion-dollar semiconductor fabrication facilities.


At Applied Materials, your work will directly influence customer outcomes and business success. As a focused and highly collaborative team, every member plays a meaningful role in shaping both technical solutions and company direction.


No two days are the same. You'll face new challenges, learn continuously, and contribute to solving some of the most difficult problems in industrial AI and optimization. Our customers engage us because they need solutions that go beyond conventional approaches, giving our team the opportunity to create truly unique and impactful technology.

Skills

NumPy, Polars, Python, Scikit-learn, Sklearn, Statistical, Statistics, pandas

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