
Leading company in the software industry
Data Scientist
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.
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关于Applied Materials

Applied Materials
PublicApplied Materials, Inc. is an American corporation that supplies equipment, services and software for the manufacture of semiconductor chips for electronics, flat panel displays for computers, smartphones, televisions, and solar products.
10,001+
员工数
Santa Clara
总部位置
$57B
企业估值
评价
10条评价
3.8
10条评价
工作生活平衡
3.2
薪酬
3.5
企业文化
3.8
职业发展
3.3
管理层
3.9
72%
推荐率
优点
Supportive and approachable management
Good benefits and training programs
Cutting-edge technology and interesting projects
缺点
Heavy workload and frequent overtime
Fast-paced and stressful environment
Limited growth opportunities
薪资范围
53个数据 点
Junior/L3
L2
L6
M3
M4
M5
M6
Senior/L5
Staff/L6
L3
L4
L5
Junior/L3 · Data Scientist I
0份报告
$153,792
年薪总额
基本工资
-
股票
-
奖金
-
$130,723
$176,861
面试评价
4条评价
难度
3.0
/ 5
时长
14-28周
面试流程
1
Application Review
2
Recruiter Screen
3
Technical/Hiring Manager Interview
4
Final Round Interview
5
Offer
常见问题
Technical Knowledge
Behavioral/STAR
Past Experience
Problem Solving
Culture Fit
最新动态
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News
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·
1w ago
Exclusive: US orders chip equipment companies to halt some shipments to China's No. 2 chipmaker Hua Hong - Reuters
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News
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1w ago
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·
1w ago