Data Scientist - EMEA

# 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.

While this role is advertised in the Netherlands, we’d love to hear from you if you’re based near any of our Applied Materials hubs across Europe, ideally within commuting distance of an Applied Materials office.

# 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, Polars, NumPy, Scikit-learn, and related analytical tooling.

• Experience with feature engineering, exploratory analysis, and model evaluation.

• Understanding of optimization techniques, statistical experimentation, and hypothesis testing.

• Strong problem-solving and analytical thinking skills.

• Ability to communicate technical concepts to diverse stakeholders.

# Preferred Skills

• Experience with discrete-event simulation or operations research.

• Experience with manufacturing, scheduling, supply chain, or industrial systems.

• Familiarity with machine learning deployment and MLOps concepts.

• Experience working with high-dimensional or time-series datasets.

• Knowledge of semiconductor manufacturing or advanced industrial environments.

# About the Team

You will be joining a highly experienced team of data scientists, AI engineers, software developers, and cloud architects, many with over a decade of experience delivering innovative solutions across multiple industries. Our work spans embedded software, renewable energy optimization, advanced scheduling systems, and AI-driven decision support platforms for multi-billion-dollar semiconductor fabrication facilities.

At Applied Materials, your work will directly influence customer outcomes and business success. As a focused and highly collaborative team, every member plays a meaningful role in shaping both technical solutions and company direction.

No two days are the same. You'll face new challenges, learn continuously, and contribute to solving some of the most difficult problems in industrial AI and optimization. Our customers engage us because they need solutions that go beyond conventional approaches, giving our team the opportunity to create truly unique and impactful technology.

## Qualifications

### Education:

Bachelor's Degree

### Skills

### Certifications:

### Languages:

### Years of Experience:

4 - 7 Years

### Work Experience:

## Additional Information

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### Shift:

Day (Netherlands)

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### Travel:

Yes, 20% of the Time

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### Relocation Eligible:

No

### Referral Payment Plan:

Employee Referral (Standard)

Salary Range:

€0.00 - €0.00

The salary offered to a selected candidate will be based on multiple factors including location, hire grade, job-related knowledge, skills, experience, and with consideration of internal equity of our current team members. In addition to a comprehensive benefits package, candidates may be eligible for other forms of compensation such as participation in a bonus and a stock award program, as applicable.

For all sales roles, the posted salary range is the Target Total Cash (TTC) range for the role, which is the sum of base salary and target bonus amount at 100% goal achievement.

Applied Materials is an Equal Opportunity Employer committed to diversity in the workplace. All 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.