Data Analysis Engineer – Remote Work Possible

Capgemini

. Develop statistical models, calibration algorithms, and data analysis methods for complex measurement and validation processes .

Posted 11/4/2026full-timeDüsseldorf • GermanyMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing statistical models, calibration algorithms, and data analysis methods, with a strong focus on optimizing scalable data analysis pipelines in high-performance computing environments. Proficient in Python and statistical modeling, with the ability to communicate technical findings effectively to interdisciplinary stakeholders.

Highest-signal resume keywords

Statistical ModelingMachine LearningData AnalysisPython ProgrammingHigh-Performance Computing

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical ModelingMachine LearningData AnalysisNumerical Linear AlgebraAlgorithm DevelopmentCalibration AlgorithmsData VisualizationAutomated ValidationBenchmarkingTesting Tools

Soft Skills

CommunicationInterdisciplinary Collaboration

Tools & Technologies

PythonNumPySciPyMatplotlibData Analysis PipelinesHPC Environments

Industry Keywords

Data ScienceComputational ScienceScientific SimulationOptimization Tools

Tech Stack

Tools & technologies

NumpyPython

About the role

Key responsibilities & impact

Develop statistical models, calibration algorithms, and data analysis methods for complex measurement and validation processes
Design, implement, and optimize scalable data analysis pipelines for high-performance computing (HPC) environments
Develop automated validation and testing tools for algorithms, measurement systems, and calibration processes
Analyze, visualize, and evaluate large datasets, deriving sound insights to optimize algorithms and systems
Document results
Conduct benchmarking and validation studies
Present technical findings to interdisciplinary stakeholders

Requirements

What you’ll need

University degree in mathematics, computer science, data science, physics, computational science, or a comparable field
Relevant professional experience developing and optimizing algorithms, statistical models, or data analysis tools in a scientific or industrial environment
Excellent knowledge of statistical modeling, machine learning, data analysis, and numerical linear algebra
Excellent knowledge of Python, NumPy, SciPy, and Matplotlib
Experience with scalable data analysis pipelines, HPC environments, automated validation methods, or scientific simulation and optimization tools is an advantage
Proficiency in German and English, both written and spoken

Benefits

Comp & perks

Professional development programs, specialized training, and mentoring
Work on innovative projects
Flexible work location, depending on project requirements and team arrangements
Flexible working hours
Work across various locations
Work in a diverse and open team
Support through a wide range of learning opportunities for professional and personal development