Data Scientist

Posted Yesterday
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Bangalore, Bengaluru Urban, Karnataka, IND
In-Office
Senior level
Artificial Intelligence • Semiconductor • Manufacturing
The Role
Design, develop, and deploy ML and AI analytics for PLM, BOM, and lifecycle risk using large enterprise datasets. Integrate Teamcenter and SAP data, build scalable Databricks/Spark solutions, create Tableau dashboards, lead projects, mentor junior staff, and enable data-driven product and release decisions.
Summary Generated by Built In

Who We Are

Applied Materials is a global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips – the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world – like AI and IoT. If you want to push the boundaries of materials science and engineering to create next generation technology, join us to deliver material innovation that changes the world. 

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

Job Summary:

As a Data Scientist, you will design, develop, and deploy advanced analytics and AI-driven solutions to analyze large-scale engineering, PLM, and BOM datasets. Your work will enable early identification of product, part, and lifecycle risks and support data-driven decision-making before and after product release.

This role partners closely with Released Product Engineering, Design Engineering, PLM, Manufacturing, Safety, Quality, and Reliability teams. You will translate complex data from enterprise systems such as Teamcenter and SAP into actionable insights, scalable analytics solutions, and interactive dashboards.

In addition to hands-on technical contributions, you will lead analytics initiatives, mentor junior team members, and help shape how data science influences engineering, release, and risk decisions at scale.

Key Responsibilities
  • Develop and implement advanced statistical, machine learning, and AI models for BOM, part, supplier, and lifecycle risk analytics
  • Analyze and integrate data from enterprise systems including Teamcenter PLM, SAP (E, and other engineering data sources
  • Design, build, and deploy scalable analytics solutions using Databricks and Spark-based platforms
  • Lead end-to-end data science projects, including data discovery, feature engineering, model development, deployment, and monitoring
  • Build and maintain dashboards and analytics applications using Tableau and low-code platforms such as Mendix
  • Enable data-driven decision-making for product readiness, new part release monitoring, and option optimization
  • Collaborate with cross-functional engineering, manufacturing, and IT teams to translate complex datasets into clear, actionable insights
  • Mentor junior data scientists and establish best practices for modeling, validation, and analytics governance
  • Stay current with emerging data science, AI, and enterprise analytics trends
Required Qualifications
  • 6+ years of full-time experience as a Data Scientist or in an equivalent analytics role
  • Postgraduate degree in Data Science, Computer Science, Statistics, Engineering, or a related field
  • Strong foundation in machine learning, statistical modeling, and data analysis techniques
  • Proficiency in Python; strong SQL skills preferred
  • Experience working with large, structured enterprise datasets
  • Hands-on experience with Databricks, Apache Spark, or similar big data platforms
  • Experience integrating and analyzing data from Teamcenter, SAP, or other PLM / ERP systems
  • Strong experience building dashboards and visual analytics using Tableau
  • Exposure to low-code or app-based analytics platforms such as Mendix is a plus
  • Strong communication skills and ability to collaborate with cross-functional teams
Why Join This Role
  • Work on high-impact engineering, PLM, and product analytics problems
  • Influence early product, release, and risk decisions using data and AI
  • Collaborate with senior engineering, manufacturing, and leadership stakeholders
  • Opportunity to scale analytics solutions from pilot initiatives to enterprise-wide adoption
  • Be part of a team shaping the future of data-driven engineering and release decisions

Additional Information

Time Type:

Full time

Employee Type:

Assignee / Regular

Travel:

Yes, 10% of the Time

Relocation Eligible:

Yes

Applied Materials is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.

Skills Required

  • 6+ years of full-time experience as a Data Scientist or equivalent analytics role
  • Postgraduate degree in Data Science, Computer Science, Statistics, Engineering, or related field
  • Strong foundation in machine learning, statistical modeling, and data analysis techniques
  • Proficiency in Python
  • Strong SQL skills
  • Experience working with large, structured enterprise datasets
  • Hands-on experience with Databricks, Apache Spark, or similar big data platforms
  • Experience integrating and analyzing data from Teamcenter, SAP, or other PLM / ERP systems
  • Strong experience building dashboards and visual analytics using Tableau
  • Exposure to low-code or app-based analytics platforms such as Mendix
  • Strong communication skills and ability to collaborate with cross-functional teams

Applied Materials Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Applied Materials and has not been reviewed or approved by Applied Materials.

  • Strong & Reliable Incentives Annual and performance bonuses are often characterized as generous and predictable, with multiple programs (AIP/DBI/SIP) explicitly highlighted. Feedback suggests these incentives meaningfully augment base pay across many roles.
  • Equity Value & Accessibility Restricted Stock Units and an employee stock purchase plan are standard components of offers, and strong stock performance has made equity a notable upside. In some roles, RSUs and refreshers provide a meaningful boost to total compensation.
  • Healthcare Strength Comprehensive medical, dental, and vision coverage, alongside EAP support and on‑site/virtual health centers in key locations, are emphasized as part of a robust package. Benefits typically start on day one, and the breadth of coverage is highlighted as a core strength.

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The Company
HQ: Santa Clara, CA
23,282 Employees
Year Founded: 1969

What We Do

Applied Materials is the leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. Our expertise in modifying materials at atomic levels and on an industrial scale enables customers to transform possibilities into reality. At Applied Materials, our innovations make possible a better future.

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