Merve Bozo, Data Scientist and Software Developer in San Jose, United States
Merve Bozo

Data Scientist and Software Developer in San Jose, United States

Member since March 11, 2019
Experienced Machine Learning Engineer takes pleasure in revealing the story of data and building predictive models with a proven track record of designing and implementing pipelines for extracting, validating, cleaning, transforming, and modeling data. Passionate about solving real-world industry problems and eager to take on new challenges and opportunities.
Merve is now available for hire

Portfolio

Experience

Location

San Jose, United States

Availability

Full-time

Preferred Environment

Git, PyCharm, Jupyter Notebook, Linux, Windows, Amazon EC2, Jira, Slack

The most amazing...

...an automated machine learning tool that leverages the power of meta-learning to select the most optimal algorithm and its parameters, adapting to any task.

Employment

  • Data Scientist

    2019 - 2022
    Turkish Aerospace Industries
    • Developed a dashboard-based surveillance system to improve a factory's work processes using IP camera recordings. Applied video and image processing algorithms using the OpenCV library together with object detection and object tracking algorithms.
    • Built an LSTM-based model to identify people's actions and improve work processes in a factory.
    • Developed a predictive maintenance model using ARIMA and LSTM algorithms which provides insight into a plane part's breakdown using the time-series data of a plane component. Applied data manipulation, analysis, and visualization.
    Technologies: Computer Vision, Data Mining, Data Science, Deep Learning, Git, Jira, Python 3, Object Detection, Object Tracking, Time Series Analysis, MySQL, PostgreSQL, PyTorch, Long Short-term Memory (LSTM), Bash Script, Keras, PyCharm, Windows, Jupyter Notebook, Neural Networks, Scikit-learn, Matplotlib, Visualization, Seaborn, SQL, Data Pipelines, Data Structures, Time Series, Data Visualization, Software Engineering, Convolutional Neural Networks, Design, Image Analysis, Data, Data Analysis, Machine Learning, Python, Predictive Modeling, Pandas, Data Modeling, Data Processing, Version Control Systems, Models, Modeling, Communication, Data Analytics, Unsupervised Learning, Supervised Machine Learning, Regression, Classification, Decision Trees, Artificial Intelligence (AI), Data Engineering, CSV, Reports
  • Machine Learning Engineer

    2016 - 2019
    Vitus Commodities
    • Took part in several data scraping projects using Selenium, API calls, the requests library, and more.
    • Created reports on Microsoft Power BI for data visualization.
    • Implemented a multilayer perceptron model using Python and Keras to forecast the natural gas demand in the UK for the coming days.
    • Deployed an LSTM model that predicts Turkey's electricity price for the next few days.
    • Implemented a scraper to obtain and manipulate GFS weather data to use as a source for model training.
    • Investigated deep learning methods to enhance the performances of the current working models for time-series data.
    • Implemented an outlier detection project consisting of probabilistic and clustering-based algorithms and an autoencoder method to detect extreme days concerning the UK's natural gas demand.
    Technologies: Slack, Jira, Git, Plotly, Selenium, RapidMiner, Keras, PyTorch, Microsoft Power BI, MySQL, Python, Amazon Web Services (AWS), Amazon S3 (AWS S3), Amazon EC2, Long Short-term Memory (LSTM), Gated Recurrent Unit (GRU), XGBoost, Data Visualization, Data Science, Data Scraping, Time Series Analysis, Time Series, PyCharm, Windows, Neural Networks, Scikit-learn, Matplotlib, Visualization, Slack API, Statistics, Seaborn, SQL, Data Pipelines, AWS RDS, Data Structures, Data Mining, Software Engineering, Convolutional Neural Networks, Design, Data Analysis, Machine Learning, Predictive Modeling, Pandas, Data Modeling, Data Processing, Web Scraping, Version Control Systems, Models, Modeling, Communication, Data Analytics, Supervised Machine Learning, Regression, Classification, Decision Trees, Decision Modeling, Data-driven Decision-making, Artificial Intelligence (AI), APIs, Data Engineering, Dashboards, CSV, Reports
  • Machine Learning Engineer

    2016 - 2017
    Independent Work
    • Implemented data preprocessing, data imputation, feature extraction, and model creation modules for the Vitriol project using Scala.
    • Researched and tested a meta-learning strategy to predict the best model with the best parameters for a given problem using Scala and Spark.
    • Implemented a parser to handle unstructured data that comes from different sources using Python.
    • Worked with big data using Apache Spark framework and Scala.
    Technologies: Git, PostgreSQL, Spark, Scala, Python, Python 3, Data Science, Spark ML, Matplotlib, Visualization, Seaborn, Data Pipelines, Data Structures, Data Mining, Data Analysis, Machine Learning, Predictive Modeling, Data Modeling, Data Processing, Models, Modeling, Data Analytics, Supervised Machine Learning, Regression, Classification, Decision Trees, Decision Modeling, Data-driven Decision-making, Artificial Intelligence (AI), CSV
  • Software Developer

    2015 - 2015
    C3S Command Control & Cybernetic Systems
    • Developed connector reliability testing software that controls the connection between PCI cards and connectors on the Linux platform.
    • Built software that calculates how much time an employee spends at the office.
    • Wrote SQL database queries to analyze an employee's working schedule.
    Technologies: MySQL, Python, C++, Linux, PostgreSQL, SQL
  • Software Test Developer

    2014 - 2014
    Taleworlds Entertainment
    • Developed automated tests for Mount&Blade: Bannerlord II project.
    • Monitored test results and reported bugs found in prerelease software on a daily basis.
    • Performed unit tests and integration tests to determine if the game scenes were working correctly.
    • Worked within an Agile environment with multiple teams.
    Technologies: Git, Unity, C++
  • Software Developer

    2014 - 2014
    TUBITAK | The Scientific and Technological Research Council of Turkey
    • Developed a parental control tool for Pardus, a Linux distribution supported by the Turkish government.
    • Implemented content filter, usage control, and monitoring modules.
    • Gained experience in open-source development and the security field.
    Technologies: PyQt, Bash, Python, Linux, Bash Script

Experience

  • Vitriol
    http://senior.ceng.metu.edu.tr/2016/mallorn/

    This is an automated machine learning tool that uses machine learning and data mining techniques for preprocessing data and choosing the machine learning model automatedly for a given problem.

    I used a meta-learning strategy to select the most appropriate algorithm and its parameters. This project is implemented in Spark and the Scala programming language to handle big data.

  • Natural Gas Demand Forecasting

    This project aims to predict the UK's gas demand using several techniques, such as feature engineering and data augmentation.

    First, I implemented an extreme day detection module to label the data as extreme or not extreme. An oversampling method helped enhance extreme days because they were a small portion of the data. I also implemented a dynamic weighted ensemble model using a multilayer perceptron (MLP) and a linear regression model to consider both linear and non-linear trends.

  • Stock Price Prediction

    The goal of the project is to predict stock prices over the Frankfurt Stock Exchange, including those for BMW and Daimler. I built RNN, GRU, and LSTM models in PyTorch because it is a time series problem.

  • Denoising of Images

    In this project, I mainly implemented various generative networks, and their components to perform unsupervised learning for the generation of new data samples (images) and, the denoising of images.

  • PriceTag

    This project aims to predict the market prices of products in several domains using pictures and their corresponding market values. I trained a convolutional neural network to predict the price of a given product using Python and Keras.

  • Pardus Gozcu

    This is a parental control tool consisting of content filtering, usage time controlling, usage management (for allowing/blocking a set of software types), and monitoring to watch and report user activities. It is an open-source project developed for Pardus, a Linux distribution, using PyQt, Python, and Bash.

Skills

  • Languages

    Python, SQL, Python 3, Bash, Scala, C++, Haskell, Bash Script, R, XML
  • Libraries/APIs

    Matplotlib, Scikit-learn, Pandas, PyTorch, Keras, Slack API, XGBoost, NLTK, Spark ML, PyQt, Beautiful Soup, TensorFlow
  • Tools

    Microsoft Power BI, PyCharm, Slack, Git, Seaborn, Plotly, Jira
  • Paradigms

    Data Science
  • Other

    Machine Learning, Predictive Modeling, Data Processing, Web Scraping, Google Colaboratory (Colab), Regression, Classification, Decision Trees, Artificial Intelligence (AI), CSV, Computer Vision, Metric Learning, Time Series, Data Mining, Visualization, Deep Learning, Statistics, Object Detection, Object Tracking, Time Series Analysis, Data Visualization, Software Engineering, Convolutional Neural Networks, Image Analysis, Neural Networks, Data Structures, Data Analysis, Data Modeling, Version Control Systems, Models, Modeling, Communication, Data Analytics, APIs, Data, Unsupervised Learning, Supervised Machine Learning, Decision Modeling, Data-driven Decision-making, Data Engineering, Dashboards, Reports, Remote Sensing, Natural Language Processing (NLP), Cloud Services, Design, Machine Learning Automation, Gated Recurrent Unit (GRU), Generative Adversarial Networks (GANs), Long Short-term Memory (LSTM), Data Scraping, Feature Analysis, AWS RDS, Sentiment Analysis
  • Frameworks

    Selenium, Spark
  • Platforms

    Windows, Linux, Jupyter Notebook, RapidMiner, Amazon EC2, Amazon Web Services (AWS)
  • Storage

    MySQL, Data Pipelines, PostgreSQL, Amazon S3 (AWS S3), JSON

Education

  • Master's Degree in Computer Engineering
    2017 - 2020
    Istanbul Technical University - Istanbul, Turkey
  • Bachelor's Degree in Computer Engineering
    2012 - 2016
    Middle East Technical University - Ankara, Turkey

Certifications

  • Using Python to Access Web Data
    FEBRUARY 2023 - PRESENT
    Coursera
  • Structuring Machine Learning Projects
    OCTOBER 2022 - PRESENT
    Coursera
  • Convolutional Neural Networks
    SEPTEMBER 2022 - PRESENT
    Coursera
  • Practical Time Series Analysis
    SEPTEMBER 2019 - PRESENT
    Coursera
  • Fundamentals of Visualization with Tableau
    SEPTEMBER 2019 - PRESENT
    Coursera
  • Google Cloud Platform Big Data and Machine Learning Fundamentals
    AUGUST 2019 - PRESENT
    Coursera
  • Neural Networks and Deep Learning
    SEPTEMBER 2018 - PRESENT
    Coursera
  • Machine Learning Foundations: A Case Study Approach
    NOVEMBER 2016 - PRESENT
    Coursera

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