Básico
Senior Data Scientist / Machine Learning Expert
Publicado: 18.05.2026
Fecha de cierre: 02.07.2026
Referencia laboral: 2f78adca6391106ab02c2b3c7bc2607a
Información del puesto
Ubicación
Veldhoven, The Netherlands
Compañía
Qreer
Referencia laboral
2f78adca6391106ab02c2b3c7bc2607a
Tipo de listado
Básico
Se requiere permiso de trabajo de la UE
No
Publicado
18.05.2026
Fecha de cierre
02.07.2026
Descripción del puesto
Are you the experienced dataIntroductionAre you the experienced datascientist that can generate actionable insights from Big Data by advancedmodeling? Are you able to identify, develop and apply the most effective and robust machinelearning approach to analyze complex machine data and apply the results toimprove performance and diagnostics capabilities? Do you consider it part ofyour job to inspire others and share your knowledge with your colleagues, thenread on!Job MissionAs a Senior Data Scientist you areresponsible for: - Technical leadership within projects - Breakdown the challenge into project work items and superviseprogress - Provide guidance to the (jr) data scientists in how to apply advanced dataanalytics methods dependent on the nature of the challenge, the expectedinsights to be gained, and the quality, density and quantity of available data - Work closely with domain experts to find and validate causal relations andto interpret predictive models - Ensure documentation and knowledge sharing at various levels in theorganization - Safeguard quality output of the data science team - Competence leadership for data science - Share your knowledge and insights with colleagues from different disciplines - Help build a dedicated data science training curriculum together with thegroup lead - Apply and further develop methodologies and models to help the team find theright approach per challenge type - Leverage your professional network to accelerate knowledge and skillsbuild-up Job DescriptionYou will be working in amulti-disciplinary team of data scientists, physicists, computer scientists,and engineers to uncover causal relationships between equipment parameters andsystem performance. Implement (un-)supervised machine learning models on thehigh-dimensional feature space of the most advanced microlithography machinesaround the globe, for which you can leverage a high-performance computercluster that ranks in the top 100 of the world. EducationPhD in Machine Learning, DataScience, Applied Statistics, Applied Mathematics, Econometrics or relatedPersonal skills - Proven track record with >5years of experience in Advanced Data Analytics and/or Statistical MachineLearning on structured and unstructured data, preferably in the high-techsector - Advanced skills and knowledge in Statistical Modeling and Predictive Modeling,excellent coding skills using state-of-the-art machine learning libraries (e.g.Python/R) - Hands-on experience with large-scale computing and machine learningmodel deployment in production - - Experience or affinity with finding causality in signals, developingpredictive models, capturing uncertainty in models, interactive visualizationand user interaction - Innovation mindset, capable ofproviding creative and good quality (robust and effective) solutions Context of the position - Within ASML, the sectorDevelopment & Engineering is responsible for the development, specificationand design of new ASML products. - Within Development & Engineering, the CSI department delivers andadvances state-of-the- art methods and techniques for the structural improvementof the performance and quality of scanner components. - The holder of this position reports to the manager of CSI Data Science &Engineering group.
Habilidades
apply blended learning
apply for research funding
apply research ethics and scientific integrity principles in research activities
build recommender systems
Business Analytics
Business Intelligence
collect ICT data
communicate with a non-scientific audience
Computational Biology
Computer Simulation
conduct research across disciplines
create data models
Data Engineering
data ethics
Data Mining
Data Models
data quality assessment
Data Science
data visualisation software
define data quality criteria
deliver visual presentation of data
demonstrate disciplinary expertise
design database in the cloud
design database scheme
develop data processing applications
develop professional network with researchers and scientists
Digital Curation
disseminate results to the scientific community
draft scientific or academic papers and technical documentation
empirical analysis
establish data processes
evaluate research activities
execute analytical mathematical calculations
Hadoop
handle data samples
Healthcare Analytics
image recognition
implement data quality processes
increase the impact of science on policy and society
information categorisation
Information Extraction
integrate gender dimension in research
integrate ICT data
interact professionally in research and professional environments
interpret current data
LDAP
LINQ
make data-driven decisions
manage data
manage data collection systems
manage findable accessible interoperable and reusable data
manage ICT data architecture
manage ICT data classification
manage intellectual property rights
manage open publications
manage personal professional development
manage research data
Marketing Analytics
mathematical modelling
MDX
mentor individuals
multidisciplinary research
N1QL
normalise data
online analytical processing
operate open source software
perform data cleansing
perform data mining
perform project management
perform scientific research
promote open innovation in research
promote the participation of citizens in scientific and research activities
promote the transfer of knowledge
publish academic research
quantitative analysis
query languages
report analysis results
Research Design
resource description framework query language
Scientific Computing
scientific literature
Social Network Analysis
SPARQL
speak different languages
State Estimation
statistical modeling techniques
Statistics
synthesise information
teach in academic or vocational contexts
think abstractly
Unstructured Data
use data processing techniques
use databases
use spreadsheets software
visual presentation techniques
write scientific publications
XQuery