OThman M. Benomar Master Plasma Physics (Hons), PhD Physics (Orsay University – France) Citizenships: France, Morocco Current residence country: Japan			www.linkedin.com/in/othman-benomar https://othmanbenomar.dev https://github.com/OthmanB
	Profile	Data Scientist | ML/Data Engineer | Data Modeler | Astrophysicist
	Visa status	Japanese working Visa (1^st July 2019 – 23 August 2025), Thai marriage Visa (unlimited)
	Summary · Specialising in creating comprehensive end-to-end data solutions since 15+ years. Delivered solutions for governments and academia. Skilled in managing the entire lifecycle of scientific solutions, from initial design and cost evaluation to product development and team resource allocation. · Led international scientific collaborations in several renowned research institutes. Prepared and refereed a 100+ research papers in top-tier scientific journals, grants, and proposals. Participated to design decisions and implementations of the next generation of space telescopes. Managed and delivered lecture courses at bachelor and master level. Supervised tens of research projects for undergrad and PhD students. Presented research, project designs at conferences and research institutes around the world for 15+ years. · Built out delivery pipelines for timeseries analysis and near-real time data science products, with monitoring system for errors Design, comprehensive stress tests of pipelines/ infrastructure/algorithms guaranteeing that set specifications are met in the context of Space missions CoRoT (CNES), Kepler (NASA) and PLATO (ESA) Design, comprehensive stress tests of pipelines/ infrastructure/algorithms guaranteeing that set specifications are met. · Devise appropriate security measures (firewalls, API gateways, VPN) for multiple compute and data architectures (AWS, Supercomputers, Clusters, PC) and OS (Mac, Linux, Windows, DSM). · Involved in the design, development, and delivery of tens of data science and data analysis algorithms for space science. Making use of complex statistical analysis, mathematical optimization, asteroseismic inversion techniques, various machine learning and deep learning algorithms. · Outside working hours: Operating blockchain infrastructure on Bitcoin, Ethereum, Cardano, Iagon, Hydra. Involvement in translations, documentation, and education in blockchain ecosystems. Cardano Blockchain Certified Associate.
	Skills & abilities
	Management:	Led international research collaborations. Initiated many successful academic and commercial collaborations. Extensive grant and proposal writing. Conference and workshop organizer. Reviewer for various international research organizations and journals. Student supervisor. Lecturer and course coordinator. Contributor in public outreach events.
	Coding:	Python, C++, IDL, Fortran, SQL, GO, R, Haskell, LabView, Mathematica, MetaTrader, C-shell, Bash-shell, slurm (scripting), Git queries / workflows.
	Machine Learning:	Use of TensorFlow, PyTorch within Keras for Autoencoders, Deep Neuronal Networks, CNN, LSTM, Decision forests.
	Mathematics:	Hypothesis testing, decision making and statistical analysis, optimization, MLE, MAP, MCMC, Bayesian analysis, differential equations, tensor and matrix operations, forecasting, physics modeling, numerical simulation, decomposition analysis (PCA, Fourier and Wavelet transform…), filtering.
	Optimisation:	Multi-threading (OMP, MPI), multi-processing (CPU, GPU), asyncio, benchmarks, unit, and property-based testing.
	Visualisations:	IDL, matplotlib (Python), gnuplot, Excel, PowerPoint.
	Databases:	MySQL, MariaDB, Non-SQL database (custom-made).
	Experience
		SELF-EMPLOYED | OUTSOURCING CONTRACTOR FOR CRAFTSMAN SOFTWARE Lead data scientist | September 2024 – Now · Developing a statistical and machine learning pipeline for real-time analytics on business operations of distributed systems. Assisting DevOps and MLOps in detecting software anomalies in Kubernetes environments: system intrusions and inefficiency patterns. National Astronomical Observatory of Japan, Japan Senior researcher / data scientist | July 2019 – August 2024 · Perform space science research. Develop statistical and Machine Learning algorithms and pipelines providing insight for complex unstructured Terabyte-size data. · Supervise undergraduate, and PhD students in Data science applied to scientific research. · Publish in peer-reviewed journals, educate, and participate to international conferences. Perform outreach missions in schools and institutions regarding the importance of science. · Expert referee evaluating peers research in statistics, machine-learning and stellar physics for journals in France, UK, US, and Japan. · Current Projects: · Machine Learning for identification and evolved star’s classification. · Fast, reliable Deep Learning parameter estimation in evolved stars. · Statistical analysis of the shape stars and its root physical causes. New York University in abu dhabi, UAE Research associate | November 2015 – June 2019 · Established the Data Center for Space Science at NYUAD. · Detection and characterisation of exoplanets using statistical optimization methods on Terabyte-size data. CCD image processing and Data mining. CNN for stellar quake identification. · Successful grant for observations with the Subaru telescope for 3 days, one of the biggest in the world (operational cost of 50 000 USD/day). · Supervision of a PhD student in statistical study of signals from stars in the milky way. Japan Society for promotion of science, Japan Research Fellow affected to the University of Tokyo | October 2013 – October 2015 · Theoretical study of nuclear processes within stars. Turbulence inference in stellar cores. · Successfully secured a research grant of 11 M¥ (10% success rate). Successful 3 days observation grant at Okayama Observatory. · Teaching a full Master level class on stellar physics. · Outreach by visiting multiple high schools to promote science and technology in Japan. Physics department at the Sydney university, Australia Postdoctoral Fellow | October 2010 – October 2013 · Successful in securing an ARC grant. · Teaching practical astronomy undergrad classes. · Detection and parameters estimation of evolved stars using Bayesian model selection methods. Understanding newly discovered complex star quake patterns in space-based timeseries.
	Education
		2010, PhD in statistical methods applied to stellar plasma physics Orsay Paris Sud XI University, France Designing and creating the first ever analysis pipeline for timeseries analysis using Fourier transform and a Langevin Metropolis-Hasting Monte Carlo sampler. Utilizing Bayesian methods for space data in CoRoT and Kepler. Modeling stellar structure and evolution. 2007, MASTER IN PLASMA AND OPTIC PHYSICS Orsay Paris Sud XI University | Ecole Polytechnique, France Studying design and processes for building the next generation of nuclear (fusion) reactors. Studying diagnostic techniques in industrial and astrophysics plasmas.
	Leadership	Mentor undergrads, junior scientists, PhD students, coordinate projects: design, cost estimate, development, testing. adapting pure research papers into industrial-grade products.
	References	Contact details for references are available upon request.