Rachel M.

Bio

Software Developer & Data Scientist with mathematical and analytical thinking, and a strong background in algorithms, experienced in Full-Stack development and building ML/DL models. Fast learner with attention to detail and a passion for clean, efficient code. Thrives in collaborative environments and performs well under pressure. Seeking to contribute my technical and analytical skills to impactful projects in a dynamic tech company.

Skills

Python

.NET

React

TypeScript

Docker

Grafana

Redis

gRPC

FastAPI

TensorFlow

influxDB

DASH(plotly)

Angular

Matplotlib

AWS

Web API

Entity Framework

MySQL

Bootcamp Project

TeleCruncher

Telemetry data processing and analytics platform

Mentored by: Next Silicon

Data Science Bootcamp 2025 (Data)

Responsibilities:

Implement a gRPC service to receive telemetry, process it, and store the results in the database.
Research Task – GPU Telemetry Types & JSON Schema
InfluxDB — Fast Telemetry Writes (Multithreading/Batch Writes/Line Protocol)
Create Composite Tag Field
Build Redis Cache for Top-K Hot Keys per Schema
Add Aggregation Tables During Write Operations
Generate telemetry frames from a CSV script by adding a mode where the generator outputs frames exactly as defined in the CSV “story” .
FastAPI + Dash/Plotly Visualization Layer
Enable zoom-in navigation by performing a fresh query to the appropriate table on every zoom action
Enable zoom-in navigation by performing a fresh query to the appropriate table on every zoom action

Click to enlarge

Additional Projects

(לפרויקט הזה בעיקרון יש לי קישורים לאתר משתמשים ואתר ניהול.. אבל אין לי איך להעלות קישורים..)

2025 - Smart Music Player "TuneYourMood"

• Developed an AI-driven music recommendation app adapting playlists to user mood.

• Built with .NET Core, React, Angular, Python, MySQL, AWS S3, Docker.

• Implemented LLM-based sentiment analysis, playlist management, and JWT authentication.

• Designed a responsive UI with MUI, managed state via Redux & Hooks, deployed on Render.

2025 – Passenger Satisfaction Analysis (Data Science)

• Analyzed Kaggle flight satisfaction data to identify key factors and trends.

• Cleaned and explored data with Pandas and NumPy, trained predictive ML models using scikit-learn.

• Visualized insights with Matplotlib and Seaborn for actionable business decisions.

English Level

Fluent