Applied Materials Hiring: Data Scientist 2026:-
Applied Materials is hiring candidates for the role of “Data Scientist” in Bengaluru, India. Complete details are given below.
| Company :- | Applied Materials |
| Job Role :- | Data Scientist |
| Location :- | Bengaluru, India |
| Experience :- | 2–5 Years |
| Salary :- | As per Company Standards |
| Travel Requirement :- | Up to 10% |
| Relocation Support :- | Available |
| Last Date to Apply :- | ASAP |
Role Overview:-
As a Data Scientist, you will analyze business problems, develop machine learning models, and deliver scalable analytics solutions that drive business outcomes. You will work with structured and unstructured data, build predictive models, deploy production-ready pipelines, and collaborate with stakeholders to translate analytical insights into actionable decisions.
Educational Requirements:-
- B.E / B.Tech
- M.E / M.Tech
- B.Sc
- M.Sc
- MCA
- Or equivalent degree in:
- Computer Science
- Information Science
- Statistics
- Mathematics
- Data Science
- Related quantitative fields
Key Skills:-
Technical Skills
- Python
- SQL
- PySpark / Apache Spark
- Machine Learning algorithms and frameworks
- Statistical analysis and data wrangling
- Tableau or Power BI
- Databricks or cloud analytics platforms
- Deep Learning concepts
- NLP and LLM applications
- Feature engineering and model evaluation
- Data warehousing concepts
- Version control and workflow documentation
Soft Skills
- Analytical thinking and problem-solving
- Communication and storytelling abilities
- Collaboration with technical and business teams
- Attention to detail
- Documentation and reporting skills
- Adaptability and continuous learning
Roles & Responsibilities:-
Data Analysis & Preparation
- Analyze business problems and stakeholder requirements
- Acquire and integrate structured and unstructured data
- Perform exploratory data analysis (EDA)
- Conduct feature engineering and data preprocessing
Machine Learning Development
- Select suitable analytical and ML approaches
- Develop regression, classification, clustering, and time-series models
- Perform cross-validation and hyperparameter tuning
- Evaluate model performance and conduct error analysis
Model Deployment & Monitoring
- Deploy models and data pipelines in production environments
- Ensure scalability and maintainability of solutions
- Monitor model health and detect data drift
- Fine-tune models and pipelines to sustain performance
Visualization & Reporting
- Build reports and dashboards
- Translate analytical outputs into business insights
- Present findings and recommendations to stakeholders
Governance & Best Practices
- Follow coding and documentation standards
- Ensure reproducibility and version control
- Support responsible AI and enterprise data governance practices
Preferred Skills:-
- Experience with Databricks and cloud-based analytics platforms
- Knowledge of Generative AI and LLM applications
- Familiarity with experiment design and monitoring techniques
- Dashboard design and data storytelling capabilities
- Reusable code development and workflow automation
About Company:-
Applied Materials is a global leader in materials engineering solutions that enable the manufacturing of semiconductor chips and advanced displays. The company develops cutting-edge technologies that power AI, IoT, and next-generation electronics. With a strong focus on innovation and employee growth, Applied Materials provides a collaborative environment where engineers and scientists solve complex challenges that shape the future of technology.
Company Benefits:-
- Supportive and innovation-driven work culture
- Learning and career development opportunities
- Health and wellness programs
- Global exposure and collaboration
- Relocation assistance (eligible roles)
- Opportunity to work on advanced AI and semiconductor technologies
Applied Materials Hiring: Data Scientist 2026 Application Process:-
Interested candidates can apply from the given below link.
Apply Link:- Click Here To Apply
Note:- Only the shortlisted candidates will be notified for the further interview process.
