Анна

Anna Mamchych
Data Analysis and Machine Learning Engineer
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PROFILE

Junior Machine Learning Engineer with hands-on experience building and deploying CNN-based models for medical image classification. Developed end-to-end ML pipelines, including data preprocessing, model
training, and on-device deployment using TensorFlow Lite.Strong foundation in statistics and data analysis, with practical experience in Python, SQL, and Docker. Interested in building production-ready ML
systems and deploying models into real-world applications. Experience in building reports in Power BI and Tableau.
EXPERIENCE
Mobile ML Developer
Adam Mickiewicz University
10/2025 – 01/2026
Academic Team Project
• Developed a mobile application using Flutter and Dart with integrated TensorFlow Lite image classification model.
• Implemented on-device machine learning inference for real-time image-based object recognition.
• Collaborated within a 4-member Agile team using Scrum - managed tasks via Jira, maintained version control with Git, actively participating in code reviews and sprint workflows.
• Delivered project presentations to academic staff and industry stakeholders, clearly communicating technical concepts and results.

Machine Learning Researcher
Adam Mickiewicz University & ID-UB
04/2025 – 11/2025
Grant-funded project
• Conducted machine learning research within the Excellence Initiative – Research University grant program.
• Collected, cleaned, and preprocessed CT imaging data; created and published an annotated dataset on Kaggle (140+ img).
• Trained and evaluated multiple CNN-based models for rare brain pathology detection, achieving >90% accuracy.
• Built data processing and image analysis pipelines in Python using OpenCV and NumPy.

Programming Trainer (Children & Youth)
Coding Giants
03/2025 – Present
• Delivered programming courses for children and teenagers, covering Python, ML/AI fundamentals, C++, C#, HTML, and Scratch.
• Designed and adapted educational materials to different skill levels, improving student engagement and comprehension.

IT Department Intern
PEPCO
06/2023 – 08/2023
• Processed, transformed, and analyzed business data to support operational decision-making.
• Utilized advanced Excel features (functions, Pivot Tables) and ERP systems for data management and reporting.
• Developed interactive dashboards and reports using Power BI.
PROJECTS
• Deep Learning Strategies for Rare and Common Brain Disease Diagnostics from Medical Imaging
This project explores the statistical challenges and comparative performance of various deep learning models for the automated detection and classification of neurological diseases from Computed Tomography
(CT) and Magnetic Resonance Imaging (MRI) scans. A primary focus of this work lies in the statistical rigor of model evaluation, especially in imbalanced data settings characteristic of rare diseases. The study will employ
and statistically compare the efficacy of transfer learning approaches with custom-built CNN architectures (e.g., VGG, ResNet) using metrics particularly sensitive to low-prevalence classes, such as F1-score and Precision-
Recall curves.
• Mobile app with Machine Learning “Wasted”
The main idea of the project was to create an application that would help determine which bin to throw garbage in. As well as spread awareness of the importance of proper garbage sorting and caring for the
environment.The program allows to take a photo and, using a trained classifier, identify which trash can to throw the object in. In addition, the application provides information about trash cans, what you can/cannot
throw in them. There is also a quiz available to help you test your knowledge.
• Fahr’s disease detection with Deep Learning
This project aimed to investigate the effectiveness of various CNNs in detecting a rare brain pathology - Fahr's disease, using CT images. As part of the study, a new unique dataset was created, which will soon be
available on Kaggle. The research was funded by grant as part of the "Excellence Initiative - Research University" project and in collaboration with Professor of Adam Mickiewicz University in Poznań.
• Statistical analysis of the impact of the introduction of the "Safe Credit 2%" program on apartment prices in Poland with Python
This project aimed to show how the government's "Safe Credit 2%" programme has affected housing prices in Poland. The analysis used data on housing prices from 2010 to 2022 in the 5 largest cities of Poland,
taken from the GUS website, as well as data for 2023 on housing prices from Kaggle. The research used multiple regression analysis and repeated measures analysis.
• World Food Price Overview with Power BI
• Grocery Store Sales Report with Power BI
• Movie analysis with Tableau
SKILLS
Python (Numpy, Pandas, Scikit-learn, Requests, Flask, OpenCV, TensorFlow, PyTorch, REST API); R, C++, SQL (PostgreSQL), NoSQL (MongoDB, Neo4j), Docker

EDUCATION
MSc in Data Science (Data Analysis and Processing) The Adam Mickiewicz University of Poznan 2021 – present
BSc in Statistics and Data Analysis The Adam Mickiewicz University of Poznan 2021 – 2024
BSc in System Analysis and Management (Data Science) Foreign University 2020 – 2024
COURSES
Deep Learning for Bioscientists The University of Nottingham
Convolutional Neural Networks for Medical Images Diagnosis Udemy
Applications of AI for Anomaly Detection; Getting Started with Deep Learning NVIDIA
Umiejętności Jutra AI Google and SGH
Google Analytics for Beginners / Advanced Google Analytics Google Analytics Academy
Research4Revenue
ADDITIONAL ACTIVITIES
Speaker at:
6th CEN Conference POWER OF DATA – Shaping the Future of Life Sciences – “Deep Learning Strategies for Rare and Common Brain Disease Diagnostics from Medical Imaging”
LIV International Biometrical Colloquium Conference - "Comparing Machine Learning Methods in Detecting Fahr's Disease"
Polish National Conference of Mathematics Students "Oblicze" - "Gradient, but it's not about colors - gradient methods beyond mathematics"
Poznań Festival of Science and Art - "With Great Power Comes Great Responsibility! Artificial Intelligence in Creativity"
Organizer of Polish National Conference of Mathematics Students "Oblicze" 2026.
Vice President of KNM – Koło Naukowe Matematyków (Scientific Circle of Mathematicians), member of AI Star Scientific Circle.
Member of the Data Analysis and Processing Curriculum Committee
Volunteer at “I Love Marketing & Technology” Conference - Supporting the conference organization and coordinating the event

ACHIEVEMENTS
Impact'26 for Young Scientists - Laureate of the program sponsored by Impact CEE.
Study@Research XI Edition - Laureate of the Excellence initiative- Research University (ID-UB) grant program.
Women in Tech Camp - Participant of a 4-day camp for the most talented STEM students from Polish universities.
New Technologies for Women - Laureate of the NTDD grant program prize sponsored by Intel and Perspektywy.
Recipient of Rector’s Scholarship for top academic performance.
LANGUAGES
Polish – Fluent | English – Advanced | Italian – Beginner
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