{"id":3711606,"url":"https://alion.io/job/applied-materials-data-scientist-emea","title":"Data Scientist - EMEA","company":{"id":3903,"name":"Applied Materials","domain":"appliedmaterials.com","url":"https://alion.io/company/amat","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":87,"open_postings":267,"ghost_share":0.004,"stale_share":0.494,"repost_share":0.007,"time_to_fill_p50_days":54,"computed_at":"2026-11-04T06:34:25Z"}},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Eindhoven, Netherlands","Dublin, Ireland","Munich, Germany","Milan, Italy","Grenoble, France","Netherlands"],"countries":["NL","IE","DE","IT","FR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Machine Learning","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Polars","optional":false},{"name":"Python","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Time Series","optional":true}],"status":"live","first_seen_at":"2026-11-03T23:25:14Z","employer_posted_date":"2026-11-03","last_verified_at":"2026-11-04T17:19:55Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Who We Are\nApplied 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.\nWhat We Offer\nSalary:\n€0.00 - €0.00\nLocation:\nBernin,FRA, Dublin,IRL, Eindhoven,NLD, England-Berkshire,GBR, Grenoble,FRA, Milan,ITA, Munich,DEUYou’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.\nAt 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.\nRole Overview\nAs 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.\nThe 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.\nWhile 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.\nKey Responsibilities\nData Analysis & Insights\nCollect, process, and analyze manufacturing, simulation, and operational datasets.\nPerform exploratory data analysis (EDA) to identify trends, bottlenecks, anomalies, and opportunities for improvement.\nDevelop statistical models and analytical frameworks to support operational decision making.\nTranslate complex analytical findings into clear business recommendations.\nModeling & Optimization\nDesign, develop, and validate predictive models for forecasting, classification, anomaly detection, and optimization use cases.\nApply operations research, statistical learning, and optimization techniques to solve manufacturing challenges.\nContribute to hybrid solutions that combine analytics, machine learning, and simulation technologies.\nDesign experiments and perform rigorous analysis to validate model effectiveness and business impact.\nSimulation & Manufacturing Intelligence\nWork with simulation technologies, including discrete-event simulation (DES), to evaluate manufacturing scenarios and operational strategies.\nAnalyze simulation outputs and combine them with historical operational data.\nDevelop methodologies that improve planning, scheduling, resource utilization, and factory performance.\nCollaboration & Communication\nWork directly with customers, domain experts, and project teams to understand business requirements.\nPresent technical findings and recommendations to both technical and non-technical audiences.\nDocument datasets, methodologies, experiments, and analytical conclusions.\nContribute to customer workshops, solution design sessions, and project reviews.\nResearch & Innovation\nStay current with developments in data science, statistics, optimization, and applied machine learning.\nEvaluate emerging methodologies and identify opportunities to improve customer outcomes.\nSupport research initiatives focused on manufacturing intelligence and decision-support technologies.\nRequired Skills\nStrong foundation in statistics, mathematics, and data analysis.\nExperience developing predictive and analytical models.\nStrong Python programming skills.\nHands-on experience with Pandas, Polars, NumPy, Scikit-learn, and related analytical tooling.\nExperience with feature engineering, exploratory analysis, and model evaluation.\nUnderstanding of optimization techniques, statistical experimentation, and hypothesis testing.\nStrong problem-solving and analytical thinking skills.\nAbility to communicate technical concepts to diverse stakeholders.\nPreferred Skills\nExperience with discrete-event simulation or operations research.\nExperience with manufacturing, scheduling, supply chain, or industrial systems.\nFamiliarity with machine learning deployment and MLOps concepts.\nExperience working with high-dimensional or time-series datasets.\nKnowledge of semiconductor manufacturing or advanced industrial environments.\nAbout the Team\nYou 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.\nAt 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.\nNo 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.\nAdditional Information\nTime Type:\nFull timeEmployee Type:\nAssignee / RegularTravel:\nYes, 20% of the TimeRelocation Eligible:\nNoThe 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.\nFor 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.\nApplied Materials is an Equal Opportunity Employer. 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