Über Faten
Hi, I'm a top rated Data Scientist (Top 2% on UpWork) with expertise in the Healthcare industry. My background includes a strong focus on Time series, Prediction Modelling and Conference Paper Writing, with a particular emphasis on Technical Report writing.
My Expertise:
- Research | Custom Technical Reports (Text + Figures + Interpretation) | Code Documentation.
-Analytics, anything from data cleaning to analysis and finding insights.
- Designing, Training and Evaluating Machine Learning models for any problem.
- Collecting, Cleaning and Managing data and databases.
- Developing the data and result into a format easily representable to other employees, investors, and other researchers.
My skill set is comprehensive, including:
✅ Time Series Analysis (Sensor Signals, Accelerometer signals, ...)
✅ Biological Signals: Heart and breathing, temperature, muscle activity, brain activity, blood pressure, oxygen levels and body composition.
✅ Python (Pandas–Scikit-learn–Numpy–Scipy, Seaborn–Keras–Pytorch–TensorFlow).
✅ R (ggplot2–dplyr–tidyr –caret–Shiny–Tidyquant).
✅ Machine Learning Algorithms (PCA, K-means, Random Forest, XGboost, Logistic Regression, SVM, etc..).
✅ Deep Learning (Neural Networks, CNN, RNN, Hugging face, ...)
and also the tools:
- SQL/No-SQL: MongoDB, MySQL.
- Tableau | Power BI.
- MATLAB | R-studio.
- Git
I'm adaptable, quick, and reliable, with a sharp eye for details and excellent communication skills (6 languages). I'm eager to help you solve any data science challenges you might have.
Französisch
Muttersprachlich oder zweisprachig
Englisch
Muttersprachlich oder zweisprachig
Vor Ort möglich
Berlin (bis zu 50 km)
Projekt- und Berufserfahrung
- NFANT LabsData ScientistApril 2024 - Heute (2 Jahre und 2 Monate)NFANT Labs is a digital health company focused on improving the outcomes and lives of Neonatal infants.
- AcoraiData scientistHIGHTECHApril 2022 - April 2023 (1 Jahr)SwedenUtilized Python to automatically extract features from four cardiac sensors: ECG (Electrocardiogram), PCG (Phonocardiogram), 3-axis SCG (Seismocardiogram), and PPG (Photoplethysmogram) successfully deriving over 300 distinct features. Developed a denoising autoencoder using Pytorch to enhance signal clarity and reliability. Built a python package for data handling, processing, and machine learning using automatic pipelines. Employed algorithms to handle missing data and improve signal and data quality. Presented results to team's global head through articles, reports and presentations.
- Kuwait College of Science and TechnologyLead Data AnalystMEDIZINFebruar 2020 - März 2022 (2 Jahre und 1 Monat)I was responsible on: Coordination of data analysis team Statistical and frequency analysis of ECG and PCG signals Data analysis: Data exploratory, Data cleaning, Data visualization, Data interpretation on Python and R. Realisation of conference and journal papers of the work.
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Ausbildung und Abschlüsse
- AI FundamentalsAI Fundamentals
- Sustainability and predictive accuracy evaluation of gel and embroidered electrodes for ECG monitoring Noise in Cardiovascular SignalsSustainability and predictive accuracy evaluation of gel and embroidered electrodes for ECG monitoring Noise in Cardiovascular Signals