Algorithm Developer

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.

• Design, develop, and deploy analytics, machine learning, optimization that drive productivity, operational efficiency, customer value, and business performance.
• Analyze complex operational and field data to identify productivity opportunities, root causes, performance gaps, and high-value business improvement initiatives.
• Leverage domain knowledge in semiconductor equipment, manufacturing, service operations, diagnostics, automation, reliability, or advanced technology environments to develop scalable productivity solutions.
• Build predictive models, decision-support tools, and business cases that connect productivity improvements to customer outcomes, revenue growth, margin enhancement, quality improvements, and operational excellence.
• Collaborate with Sales, Field Service, Operations, Engineering, and customer-facing teams to identify high-value problems, define requirements, prioritize solution investments, and ensure successful deployment and adoption.
• Drive end-to-end execution from opportunity identification and solution development through implementation, adoption tracking, value realization, and continuous improvement.
• Establish performance monitoring frameworks including dashboards, KPIs, operating rhythms, and governance mechanisms to measure impact, communicate progress, and drive accountability.
• Contribute to the Analytics COE roadmap by driving innovation through advanced analytics, AI, digital productivity tools, and automation technologies.
• Ability to drill down to tool HW configuration, process, tool states, events data, other diagnostic datalogs as needed to validate tool operations, metrology/ inline data outcomes.

• Bachelor's or Master's degree in Data Science, Engineering, Mathematics, Statistics, Industrial Engineering, Operations Research, or a related technical field.
• 3 to 7 years of experience in algorithm development, analytics, machine learning, industrial engineering, productivity improvement, service operations, or related technical roles.
• Strong proficiency in Python and experience with SQL, JMP, Tableau, Power BI, Excel, or similar analytics and visualization platforms.
• Proven experience in statistical analysis, predictive/forecast modeling, optimization techniques and data-driven problem solving.
• Demonstrated ability to translate operational and business challenges into scalable analytical solutions that drive measurable outcomes.
• Experience working across cross-functional teams, influencing stakeholders, managing priorities, and supporting solution deployment and adoption.
• Strong communication, collaboration, and problem-solving skills with the ability to engage technical, operational, and business stakeholders.
• Having prior experience on Agentic AI-based solutions would be preferred.

• Solve operational and customer-facing challenges using data-driven approaches.
• Combine analytical depth with strong execution focus.
• Translate insights into decisions, actions, and measurable business outcomes.
• Effectively influence and collaborate across global cross-functional teams.
• Demonstrate ownership, innovation, and a continuous improvement mindset.