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Presentation
Physics student in final year, passionate about solving real-world problems with data and
machine learning. Experience in neural networks, classification, forecasting, regression and causal
impact analysis, with models reaching up to 97% accuracy. Seeking opportunities to apply
analytical and technical skills in data science and ML roles. I also worked a bit in web platforms using FastAPI and Flask.
machine learning. Experience in neural networks, classification, forecasting, regression and causal
impact analysis, with models reaching up to 97% accuracy. Seeking opportunities to apply
analytical and technical skills in data science and ML roles. I also worked a bit in web platforms using FastAPI and Flask.
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Offered services
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Background
Full Stack developer and analyst
-Developed causal impact regression models using time series analysis for a
FastAPI web platform (collaborative project), achieving stable confidence
intervals and up to 25% relative impact across multiple datasets.
-Built time series forecasting models (30-day projections) with controlled
confidence bands below 50% of maximum values.
FastAPI web platform (collaborative project), achieving stable confidence
intervals and up to 25% relative impact across multiple datasets.
-Built time series forecasting models (30-day projections) with controlled
confidence bands below 50% of maximum values.
Data Analyst and ML Engineer
-Developed classification and regression algorithms using softmax classifiers
and single-hidden layer neural networks (with varying neurons and activation
functions), achieving 96-97% accuracy in most exercises.
-Implemented medical image classification algorithms for disease detection,
contour analysis, and color pattern recognition, both with and without machine learning libraries. (Still in progress, degree project)
-Conducted comparative analysis of fully connected neural networks using
linear vs polynomial proposals (up to degree 3), demonstrating improved
accuracy with higher polynomial degrees after network normalization.
and single-hidden layer neural networks (with varying neurons and activation
functions), achieving 96-97% accuracy in most exercises.
-Implemented medical image classification algorithms for disease detection,
contour analysis, and color pattern recognition, both with and without machine learning libraries. (Still in progress, degree project)
-Conducted comparative analysis of fully connected neural networks using
linear vs polynomial proposals (up to degree 3), demonstrating improved
accuracy with higher polynomial degrees after network normalization.
Physic's Bachelor
I'm a last year physic's student, got a lot of experience in Machine/Deep Learning, images analysis, data science, web development and causal impact codes and bit more. My relevant courseworks were stochastic processes applied to physics, biophysics and neural networks.
🇩🇪Deutsch 🇬🇧English 🇪🇸Spanish 🇫🇷French
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Working hours
Monday
From08h00To18h00
Tuesday
From08h00To18h00
Wednesday
From08h00To18h00
Thursday
From08h00To18h00
Friday
From08h00To18h00
Saturday
Closed
Sunday â–ª Today
Closed
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