Yasaman Najafi Jozani-Research Data Scientist
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Experience
Research Data Scientist
RWTH Aachen University
- Led large-scale data analysis on high-volume event data, applying statistical modeling and time-series methods to detect weak signals in noisy environments
- Designed and maintained scalable Python data pipelines for real and simulated datasets, optimizing signal detection and background estimation at scale
- Applied advanced statistical inference techniques (likelihood-based modeling, hypothesis testing) to support quantitative decision-making
- Deployed data-processing workflows on HPC clusters using Slurm, enabling parallelized analysis and large-scale batch execution
- Built reproducible, version-controlled data workflows using Python, Bash, and Git to ensure reliability and traceability of results
- Translated complex experimental data into actionable insights, enabling quantitative decision-making
Big Data Analyst – KiDS-1000 Survey
University of Bonn
- Analyzed large-scale, high-dimensional datasets using Python-based pipelines, focusing on data validation, modeling, and reproducibility
- Corrected for systematic effects and validated complex multi-step data pipelines for reproducible results
- Applied statistical and quantitative methods to extract meaningful insights from high-dimensional datasets
- Contributed to peer-reviewed publication in Astronomy & Astrophysics, highlighting data-driven results
Intern – Data & Signal Analysis
Max Planck Institute for Radio Astronomy
- Processed and analyzed high-frequency telescope data, focusing on signal polarization and noise reduction
- Developed Python tools for data cleaning, visualization, and automated analysis workflows
- Applied quantitative techniques to extract meaningful patterns from complex observational datasets
Data Analyst – Statistical Modeling
Sharif University of Technology
- Processed and analyzed high-dimensional, large-scale scientific datasets to extract meaningful quantitative insights
- Applied Bayesian inference and likelihood-based statistical modeling to validate hypotheses and support decision-making
- Built reproducible Python data pipelines for automated handling of complex datasets
Industry Experience
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Experienced in Education.
Business Area Experience
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Experienced in Research and Development.
Skills
- Python
- Sql
- Time Series
- Large-Scale Data Analysis
- Statistical Modeling
Programming
- Python
- Bash
- Sql
- C/C++
Data Analysis & Ml
- Numpy
- Pandas
- Scipy
- Scikit-Learn
- Tensorflow
Scientific Computing
- Astropy
- Awkward Array
- Iminuit
Visualization
- Matplotlib
Tools & Platforms
- Git
- Jupyter
- Linux
- Conda
- Latex
Hpc & Automation
- Slurm
- Parallel Batch Jobs
- Large-Scale Data Processing On Hpc Clusters
Languages
Education
RWTH Aachen University
Data Analysis Research in Experimental High Energy Physics · Aachen, Germany
University of Bonn
Master in Astrophysics · Astrophysics · Bonn, Germany
Sharif University of Technology
Bachelor in Physics · Physics · Tehran, Iran, Islamic Republic of
Certifications & licenses
European School Of High-Energy Physics
CERN / CERN–ESA, Grenaa, Denmark
Deep Learning School
ErUM-Data-Hub, Germany
Statistics
Experience
Global Experience
Expertise
Qualifications
Profile
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