About 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.
French
Native or bilingual
English
Native or bilingual
Can work on-site
Berlin (up to 50km)
Experience
- NFANT LabsData ScientistApril 2024 - Today (2 years and 2 months)NFANT Labs is a digital health company focused on improving the outcomes and lives of Neonatal infants.
- AcoraiData scientistTECHApril 2022 - April 2023 (1 year)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 AnalystMEDICALFebruary 2020 - March 2022 (2 years and 1 month)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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Education
- 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