Who We Are
Applied Materials is the global leader in materials science and engineering solutions that are at the foundation of virtually every new semiconductor chip and advanced display in the world. The equipment that we create and service is essential to advancing AI and accelerating the commercialization of next-generation semiconductor chips. Join us and push the boundaries of materials science and engineering in a company at the foundation of the electronics industry. The work we do together advances the world’s technology.
What We Offer
Location:
Bangalore,IND
You’ll benefit from a supportive work culture that encourages you to learn, develop, and grow your career as you take on challenges and drive innovative solutions for our customers. We empower our team to push the boundaries of what is possible—while learning every day in a supportive leading global company. Visit our Careers website to learn more.
At Applied Materials, we care about the health and wellbeing of our employees. We’re committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go. Learn more about our benefits .
Role Overview
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
Data Analysis & Insights
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.
Modeling & Optimization
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.
Simulation & Manufacturing Intelligence
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.
Collaboration & Communication
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.
Research & Innovation
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,…