Anastasiya Kotelnikova

Data Scientist | MS in Data Science | Business + Analytics Background


Turning Data into Actionable Insights

Python | R | SQL | AWS | ML/DL | TensorFlow/Keras | PyTorch | Hadoop/MapReduce | Time Series | NLP | Git

Welcome to My Portfolio

I’m Anastasiya β€” a Data Scientist with a strong foundation in business analytics and hands-on experience building machine learning and deep learning solutions. I focus on transforming complex data into actionable insights through predictive modeling, automation, and scalable data pipelines.

This portfolio showcases projects in time-series forecasting (LSTM, GRU), large-scale data processing with Hadoop & MapReduce on AWS, applied machine learning, and neuromorphic computing using PyTorch & Norse.

Featured Projects

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🧠 Human vs AI Text Classifier

Built a machine learning model to classify text as human-written or AI-generated using a custom dataset I created and published on Kaggle (2,500 human-written vs 2,500 AI texts).

Tools: TF-IDF, Joblib, Logistic Regression, SVC, Naive Bayes, Random Forest

View on GitHub | View on Kaggle
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πŸ’Ό Equity Portfolio Optimization (R)

Simulated portfolio rebalancing using historical stock price data for a $5 million equity fund. Evaluated daily vs. periodic rebalancing performance.

Tools: R, Portfolio Theory, Time Series

View on GitHub
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☁️ AWS MovieLens MapReduce

Deployed Hadoop on AWS EC2 and executed a MapReduce job to analyze 1M+ ratings from MovieLens dataset using custom Java classes.

Tools: Java, AWS EC2, Hadoop, MapReduce

View on GitHub

⚑ Spiking Neural Networks with PyTorch

Led implementation of SNNs using PyTorch and Norse, benchmarking performance against traditional ANNs using SHD/N-MNIST datasets.

Tools: Python, Norse, Deep Learning, SNN

View on GitHub

🧬 COVID-19 Case Forecasting

Forecasted COVID-19 regional case trends using LSTM deep learning models to detect surges and support health planning.

Tools: Python, Pandas, LSTM, ML

View on GitHub

🏠 House Price Regression (R)

Built a regression model using R to predict housing prices based on historical housing data. Focused on preprocessing, model tuning, and evaluation using performance metrics like RMSE and RΒ².

Tools: R, caret, ggplot2, dplyr

View on GitHub

🌌 CMEPredict: GRU & LSTM Model Comparison

Rebuilt and evaluated GRU and LSTM models for predicting solar wind CME events using time series data (12–60 hr windows). Assessed model accuracy using confusion matrices and ROC curves.

Tools: Python, TensorFlow, Keras, GRU, LSTM, Time Series, ROC-AUC, Confusion Matrix

View on GitHub

☁️ Scalable ML Training & Inference on AWS

Designed and implemented a cloud-based machine learning pipeline for scalable model training and inference. Used Apache Spark on AWS EMR for distributed training and Docker for containerized inference, with datasets and artifactsstored in Amazon S3.

Tools: AWS (EMR, EC2, S3), Apache Spark, Docker, Python

View on GitHub

πŸ€– NovaStyle Smart FAQ Chatbot

Built an AI-powered FAQ chatbot for an e-commerce scenario using a serverless AWS architecture. Implemented AWS Lambda and API Gateway to deliver real-time responses and improve customer support automation.

Tools: AWS Lambda, API Gateway, Python, NLP

View on GitHub
Anastasiya Kotelnikova

About Me

I bring a strong interdisciplinary background spanning business, logistics, healthcare, IT, and marketing, which allows me to approach data science with both technical depth and real-world context. My work focuses on applying machine learning, cloud computing, and data analytics to transform complex problems into clear, actionable insights thatsupport strategic decision-making.

I am currently working at NJIT as an IT Technician while pursuing my MS in Data Science. In this role, I support campus technology operations, troubleshoot systems, and help streamline workflowsβ€”giving me hands-on experience with production environments, infrastructure, and user-centered problem solving alongside my academic training.

My technical experience includes designing and deploying data and machine learning solutions on AWS, working with services such as EC2, S3, IAM, and Hadoop-based processing. I have implemented scalable workflows using MapReduce, built and evaluated machine learning and deep learning models, and worked with distributed systems in both academic and applied settings.

I hold multiple AWS certifications, including AWS Certified Cloud Practitioner and AWS Associate-level certifications, which reflect my practical knowledge of cloud architecture, application development, and AI-focused services. I am particularlyinterested in machine learning, deep learning, and scalable data systems, and I am motivated by building ethical, reliable AI solutions that deliver measurable impact across industries.

Certifications

πŸ“œ Graduate Certificate in Big Data Essentials β€” NJIT, May 2025
Completed 4-course graduate-level program focused on large-scale data processing, distributed computing, and real-world applications using Hadoop, MapReduce, and Apache Spark.
View Certificate (PDF) | Verify via Parchment

☁️ Additional Certifications
AWS Certified Cloud Practitioner β€” Completed Jan 2026
View Credential

AWS Certified Developer – Associate β€” Completed Jan 2026
View Credential

AWS Certified Solutions Architect – Associate β€” Completed Jan 2026
View Credential

AWS Certified AI Practitioner – Associate β€” Completed Jan 2026
View Credential

Databricks Fundamentals Accreditation
Issued by Databricks β€” Completed Jan 2026
View Certificate (PDF)  |  Verify Credential

Or view it on GitHub or LinkedIn

πŸ“„ Download My Resume

Contact

If you'd like to connect or collaborate, feel free to reach out:

AnastasiyaKotelnikova21@gmail.com