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Viacheslav Zhenylenko, Machine Learning Developer in San Diego, CA, United States
Viacheslav Zhenylenko

Machine Learning Developer in San Diego, CA, United States

Member since June 13, 2019
Viacheslav has seven years of experience in data science and software engineering. He is passionate about the insights gained from raw data and enjoys converting them to create exceptional business value. Viacheslav's primary expertise is Python, with production experience in Java and C++. To solve data-heavy projects, he has applied advanced machine learning techniques, such as computer vision, NLP, product recommendation systems, networking data, and classical data science.
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Portfolio

  • Grata Inc.
    Python, Docker, Elasticsearch, Celery, Kubernetes, Jenkins, PostgreSQL, REST...
  • Botprise, Inc.
    Amazon Web Services (AWS), Python, Flask, MongoDB, Apache Kafka, React Redux...
  • Spin (Tier Mobility)
    Data Validation, Data Analysis, Data Analytics, Python, SQL, R, Data Science...

Experience

Location

San Diego, CA, United States

Availability

Full-time

Preferred Environment

Eclipse, VS Code, PyCharm, Jupyter, MacOS, Linux, Vim Text Editor, Sublime Text, Bash

The most amazing...

...project I've developed was an industry-first, self-reconfigurable AutoML system for congestion detection in RAN networks.

Employment

  • Senior Data Engineer

    2022 - 2022
    Grata Inc.
    • Developed end-to-end distributed NLP-based geocoding pipeline using Celery on Kubernetes.
    • Implemented scraping from company websites and aggregators.
    • Developed and deployed on the AWS SageMaker web page category classification model.
    • Implemented a hybrid geocoding model with query lookup, query relaxation, result validation, prioritization, and fallback mechanisms.
    • Used combinations of available geo databases and offline entity extractors like libpostal and third-party geocoding services to combine it in a single view.
    • Increased a fraction of parsed addresses, reduced incorrect addresses by 95%, and improved the overall data quality score by 20%.
    Technologies: Python, Docker, Elasticsearch, Celery, Kubernetes, Jenkins, PostgreSQL, REST, Geocoding, Grafana, DataOps, Datadog, Pandas, NumPy, NLTK, libpostal, GIS, React, Cloud Infrastructure, SQL, Deep Learning, Amazon Web Services (AWS), Git, Agile Software Development, Linux, Bash, Sublime Text, Vim Text Editor, Classification, Data Pipelines, Django, Jupyter, Natural Language Processing (NLP), Parallel Programming, PyCharm, Data Science, Flask, React Redux, Algorithms, Data Analysis, Python 3, NLP, SciPy, DevOps, Amazon SageMaker, Data Scraping, Software Development, Programming, Transformers, Concurrent Programming, Data Engineering, Analytics, API Integration, Data Validation, Data Visualization, Dashboards, Databases, Software Engineering, Scikit-learn, Matplotlib, Unit Testing, ETL, GeoPandas, Quality Assurance (QA)

  • Lead Data Scientist

    2020 - 2022
    Botprise, Inc.
    • Developed the back end for the full ML cycle, ModelOps, and MLOps, on the platform. Added a wrapper on top of the AWS SageMaker.
    • Worked on dozens of automation workflows (use cases), including MLOps, analytics, DataOps, networks, ITOps, etc.
    • Created the back- and front-end elements using React for a drag-and-drop, chatbot-building application.
    • Implemented and deployed dozens of algorithms (classification, clustering, time series, NLP, and computer vision) for different use cases.
    • Led a small ML team, including planning, management, monitoring, and leadership.
    Technologies: Amazon Web Services (AWS), Python, Flask, MongoDB, Apache Kafka, React Redux, REST, Docker, Kubernetes, Amazon SageMaker, SciPy, NumPy, Pandas, PyTorch, TensorFlow, Transformers, Management, PostgreSQL, Machine Learning Operations (MLOps), React, Cloud Infrastructure, SQL, Computer Vision, Deep Learning, Keras, Git, Agile Software Development, Linux, Object Detection, Convolutional Neural Networks, Bash, Sublime Text, Vim Text Editor, Anomaly Detection, Classification, Data Pipelines, AutoML, TCP/IP, Networks, Time Series Analysis, Concurrent Programming, Predictive Analytics, Jupyter, OpenCV, Predictive Modeling, Machine Learning Automation, Natural Language Processing (NLP), PyCharm, Data Science, Algorithms, Python 3, NLP, AWS CloudFormation, DataOps, Software Development, Networking, AWS Lambda, Artificial Intelligence (AI), Programming, Datadog, NLTK, Data Engineering, Analytics, API Integration, Data Validation, Data Visualization, Neural Networks, Dashboards, Databases, Software Engineering, Linear Regression, Microsoft Excel, Spreadsheets, Scikit-learn, Matplotlib, Statistical Modeling, Unit Testing, ETL, Plotly

  • Data Analyst

    2020 - 2020
    Spin (Tier Mobility)
    • Performed a time-series forecasting of the demand for e-scooters for a global e-scooter rental company (hundreds of cities) with models for auto selection and auto retraining.
    • Performed ad-hoc data analysis and built Looker dashboards.
    • Performed an intervention-effect analysis (for promotions and other events).
    Technologies: Data Validation, Data Analysis, Data Analytics, Python, SQL, R, Data Science, Data Visualization, Google Cloud, Google Cloud Platform (GCP), Looker, BigQuery, Google BigQuery, Pandas, NumPy, Git, Agile Software Development, Linux, Cloud Infrastructure, Bash, Sublime Text, Vim Text Editor, Data Pipelines, Time Series Analysis, Predictive Analytics, Jupyter, Predictive Modeling, GCP, PyCharm, Apache Airflow, Algorithms, Docker, Python 3, SciPy, Software Development, Programming, Analytics, Business Intelligence (BI), Dashboards, Databases, Software Engineering, Linear Regression, Spreadsheets, Scikit-learn, Matplotlib, Statistical Modeling, ETL, Plotly

  • Senior MLOps Engineer

    2020 - 2020
    Pro Football Focus, LLC
    • Introduced and implemented MLOps techniques, tools, and approaches.
    • Rebuilt a dozen monolithic R pipelines into distributed, modular, and functional-styled Python pipelines.
    • Developed MLOps layer on top of Dagster, Seldon, Feast, and other tools.
    • Fine-tuned existing model hyperparameters both for speed and performance.
    Technologies: Data Science, Python, R, Machine Learning, React, Python 3, Seldon, Seldon Core, Dagster, RabbitMQ, PostgreSQL, Feast, Great Expectations, Machine Learning Operations (MLOps), Cloud Infrastructure, SQL, Deep Learning, Pandas, NumPy, Amazon Web Services (AWS), Git, Agile Software Development, Linux, Bash, Sublime Text, Vim Text Editor, Classification, Data Pipelines, Explainable Artificial Intelligence (XAI), Predictive Analytics, Jupyter, Predictive Modeling, Parallel Programming, PyCharm, VS Code, Data Analytics, Apache Airflow, REST, Algorithms, Kubernetes, Docker, SciPy, Prefect, AWS CloudFormation, DevOps, Software Development, AWS Lambda, Programming, Dask, Data Engineering, Databases, Software Engineering, Linear Regression, Sports, Scikit-learn, Matplotlib, Statistical Modeling, Unit Testing, ETL, Plotly, Quality Assurance (QA)

  • Machine Learning Engineer

    2020 - 2020
    Plutoshift, Inc.
    • Introduced MLOps tools to existing infrastructure (Seldon, Feast, and Great Expectations).
    • Migrated existing hardcoded models to introduce the MLOps infrastructure.
    • Developed back-end APIs using Django for ML-related services.
    • Implemented classification and time series forecasting models for manufacturing sensors.
    Technologies: Machine Learning, Python, Django, Convolutional Neural Networks, Object Detection, TensorFlow, PyTorch, Keras, Apache Airflow, Cloud Infrastructure, Google Cloud Platform (GCP), Azure, Cassandra, Apache Cassandra, Seldon, Feast, Great Expectations, Seldon Core, SQL, Deep Learning, Pandas, NumPy, Git, Agile Software Development, Linux, Google Cloud, Bash, Sublime Text, Vim Text Editor, Anomaly Detection, Classification, Data Pipelines, Time Series Analysis, Predictive Analytics, Jupyter, Predictive Modeling, GCP, PyCharm, Data Science, Flask, REST, Algorithms, Kubernetes, Docker, Python 3, SciPy, Software Development, AWS Lambda, Programming, Datadog, Data Engineering, Data Visualization, Databases, Software Engineering, Linear Regression, Scikit-learn, Matplotlib, Statistical Modeling, Unit Testing, ETL, Quality Assurance (QA)

  • Senior AI Developer

    2019 - 2020
    Akcelita
    • Developed an ingestion and processing pipeline on AWS for photos from surveillance cameras.
    • Experimented with various non-DL and DL approaches and tested them. Trained and used the Siamese network with an attention mechanism, achieving +95% accuracy.
    • Created and shared presentations with analytics to executives. Developed and maintained a wiki for the project.
    Technologies: Amazon Web Services (AWS), TensorFlow, Python, Docker, PyTorch, AWS Lambda, Computer Vision, Deep Learning, Machine Learning, Classification, Artificial Intelligence (AI), Cloud Infrastructure, SQL, Pandas, NumPy, Keras, Git, Agile Software Development, Linux, Convolutional Neural Networks, Bash, Sublime Text, Vim Text Editor, Data Pipelines, Predictive Analytics, Jupyter, OpenCV, Predictive Modeling, PyCharm, Data Science, Algorithms, Python 3, SciPy, Software Development, Programming, Data Visualization, Neural Networks, Software Engineering, Scikit-learn, Matplotlib, Statistical Modeling, Unit Testing, ETL

  • Team Lead

    2018 - 2019
    The National Academy of Sciences of Ukraine
    • Led and mentored a team of students. I defined objectives and controlled the process using the Agile methodology.
    • Created a tool for crop classification and map creation.
    • Collected data manually and via web scraping using Mapillary and oversaw data labeling.
    • Implemented and tested DeblurGAN and several other classic deblurring methods.
    • Oversaw field localization (YOLO) and crop classification by fine-tuning a ResNet model.
    Technologies: OpenCV, PyTorch, TensorFlow, Keras, Python, Python 3, Computer Vision, Generative Adversarial Networks (GANs), Cloud Infrastructure, Deep Learning, Pandas, NumPy, Amazon Web Services (AWS), Git, Agile Software Development, Linux, Object Detection, Convolutional Neural Networks, Bash, Sublime Text, Vim Text Editor, Classification, Data Pipelines, Predictive Analytics, Jupyter, Predictive Modeling, PyCharm, VS Code, Data Science, Algorithms, Docker, SciPy, Beautiful Soup, Web Scraping, Data Scraping, Software Development, AWS Lambda, Programming, GIS, API Integration, Neural Networks, Software Engineering, Scikit-learn, Matplotlib, Statistical Modeling, Unit Testing, GeoPandas

  • Senior Data Scientist

    2017 - 2019
    Openwave Mobility
    • Created a multi-staged data pipeline from raw packet data (TCP/IP layer) to consumable inputs for machine learning models with multi-processing implementation in Python (CPython).
    • Trained, tuned, evaluated, and compared multiple machine learning models in Python (scikit-learn, Keras, XGBoost, CatBoost) and C++ (mlpack).
    • Oversaw the data analysis and communication with stakeholders. Created a reusable Python tool for generating rapid and externally configurable data analysis reports.
    • Implemented custom feature generation algorithms based on expert knowledge based on aggregation, derivatives, TCP/IP conversation delays, products, and fractions.
    • Implemented custom, multi-staged feature selection algorithms that were model-based.
    • Deployed and monitored the project in production in the network. If the tool detects congestion, optimization policies are applied. Customers reported up to a 20% increase in the quality of delivery for video content.
    Technologies: C++, Python, Python 3, Concurrent Programming, Agile Software Development, Machine Learning, Deep Learning, Time Series Analysis, Networks, Networking, TCP/IP, TensorFlow, SciPy, Scikit-learn, Pandas, NumPy, mlpack, AutoML, Explainable Artificial Intelligence (XAI), Cloud Infrastructure, SQL, Amazon Web Services (AWS), Git, Linux, Bash, Sublime Text, Vim Text Editor, Classification, Data Pipelines, Predictive Analytics, Jupyter, Predictive Modeling, Machine Learning Automation, Parallel Programming, PyCharm, Data Science, Data Analytics, Algorithms, Docker, Data Analysis, Software Development, AWS Lambda, Artificial Intelligence (AI), Programming, Data Engineering, Analytics, Data Validation, Data Visualization, Neural Networks, Databases, Software Engineering, Linear Regression, Matplotlib, Statistical Modeling, Unit Testing, ETL, Plotly

  • Data Scientist

    2015 - 2017
    Octetis
    • Developed, deployed, and evaluated a hybrid recommendation engine in Python for an online store.
    • Oversaw customer behavior analysis, visualization, and stakeholder communication.
    • Handled different scenarios of user engagement using a strategy pattern. Contextual recommendations were given based on popularity (general and category-based), item-to-item, and SVD. (Python, scikit-learn, SciPy).
    • Integrated recommendation engine into a Django back end.
    • Conducted multiple A/B tests with random sampling for evaluation of the system. Compared to the most popular items in the category baseline, we achieved up to a 150% boost in purchases per session and increased revenue.
    • Created an image super-resolution module for an online cloud site constructor with Keras.
    • Utilized middle-deep CNN, trained on several blur kernels, and deployed it as a service via REST.
    • Conducted surveys showing an increase of about 5% in satisfaction for users of the platform.
    Technologies: TensorFlow, Keras, Python, Pandas, NumPy, Python 3, PostgreSQL, Recommendation Systems, Django, Data Analysis, Data Analytics, Machine Learning, Artificial Intelligence (AI), Cloud Infrastructure, MySQL, SQL, Computer Vision, Deep Learning, Amazon Web Services (AWS), Git, Agile Software Development, Linux, Object Detection, Convolutional Neural Networks, Bash, Sublime Text, Vim Text Editor, Anomaly Detection, Classification, Data Pipelines, Time Series Analysis, Predictive Analytics, Jupyter, OpenCV, Predictive Modeling, PyCharm, Data Science, REST, Algorithms, Docker, SciPy, Jenkins, Microsoft Power BI, Software Development, AWS Lambda, Programming, Data Engineering, Analytics, API Integration, Data Validation, Data Visualization, Neural Networks, Business Intelligence (BI), Dashboards, Databases, Software Engineering, Linear Regression, Microsoft Excel, Spreadsheets, Scikit-learn, Matplotlib, Statistical Modeling, Unit Testing, ETL, Tableau, Plotly

  • Software Engineer Intern

    2015 - 2015
    Facebook
    • Trained and evaluated AdaBoost models for customer churn prediction using FBLearner Flow.
    • Performed hyper-parameters tuning for optimization.
    • Data-engineered with Hive and processed data using Python.
    Technologies: Apache Hive, Python, Python 3, Data Pipelines, FBLearner, Machine Learning, Git, Agile Software Development, Linux, Bash, Sublime Text, Vim Text Editor, Classification, Predictive Analytics, Predictive Modeling, Data Science, Data Analytics, Algorithms, Software Development, Programming, Data Engineering, Analytics, Databases, Software Engineering, ETL

  • Research Intern

    2014 - 2015
    Samsung
    • Developed algorithms for smart keyboard functionality (word prediction and spelling correction).
    • Developed Naive Bayes for n-grams and K-nearest neighbors (KNN) for spelling corrections.
    • Created tweaks for better algorithm performance using Laplace smoothing and a custom keyboard distance for KNN.
    • Developed algorithms with C++. Integrated them with a Java to Android keyboard and published them to the App Store.
    Technologies: C++, Android, Java, Machine Learning, Artificial Intelligence (AI), Natural Language Processing (NLP), Android NDK, Git, Agile Software Development, Linux, Bash, Sublime Text, Vim Text Editor, Eclipse, Data Science, Algorithms, NLP, Software Development, Programming, Software Engineering

  • Software Engineer Intern

    2013 - 2014
    Engage Point
    • Developed a Content Management Interoperability System in Jakarta EE. I used the Model-view-controller framework for the application.
    • Developed Enterprise JavaBeans for the business logic of the application.
    • Developed JavaServer Pages for the presentation level.
    Technologies: Java EE, Java, Linux, Git, Bash, Sublime Text, Vim Text Editor, Eclipse, Software Development, Programming, Software Engineering

Skills

  • Languages

    Python, SQL, Python 3, Bash, R, Snowflake, Fortran, Java, C++

  • Frameworks

    Django, Flask

  • Libraries/APIs

    Scikit-learn, Keras, TensorFlow, PyTorch, Pandas, NumPy, SciPy, Beautiful Soup, Dask, NLTK, Matplotlib, OpenCV, React Redux, PySpark, React

  • Tools

    Jupyter, PyCharm, IPython Notebook, Amazon SageMaker, Geocoding, GIS, Vim Text Editor, Sublime Text, Plotly, VS Code, Apache Airflow, Git, Celery, Jenkins, AWS CloudFormation, Grafana, Looker, Microsoft Power BI, AutoML, RabbitMQ, BigQuery, Microsoft Excel, Spreadsheets, Tableau, Android NDK

  • Paradigms

    Data Science, Agile Software Development, REST, Unit Testing, ETL, Parallel Programming, DevOps, Concurrent Programming, Anomaly Detection, Business Intelligence (BI), Management

  • Platforms

    Docker, AWS Lambda, MacOS, Amazon Web Services (AWS), Linux, Apache Kafka, Kubernetes, Eclipse, Android, Java EE, Google Cloud Platform (GCP), Azure

  • Storage

    MySQL, PostgreSQL, Data Pipelines, Data Validation, MongoDB, Elasticsearch, Datadog, Databases, Apache Hive, Cassandra, Google Cloud

  • Other

    Predictive Analytics, Predictive Modeling, Machine Learning Automation, Computer Vision, Data Analytics, Deep Learning, Machine Learning, Mathematics, Applied Mathematics, Statistics, Algorithms, Data Analysis, Dagster, Machine Learning Operations (MLOps), Prefect, Computer Science, Web Scraping, Data Scraping, Software Development, Artificial Intelligence (AI), Programming, Computational Science, libpostal, Time Series Analysis, Convolutional Neural Networks, Object Detection, Seldon, Feast, Great Expectations, Seldon Core, Data Visualization, Data Engineering, Analytics, Neural Networks, Software Engineering, Linear Regression, Statistical Modeling, GeoPandas, GCP, Recommendation Systems, Natural Language Processing (NLP), Science, Scientific Computing, NLP, DataOps, Physical Science, Networking, Physics, Applied Physics, Transformers, TCP/IP, mlpack, Explainable Artificial Intelligence (XAI), Cloud Infrastructure, Google BigQuery, API Integration, Dashboards, Quality Assurance (QA), Generative Adversarial Networks (GANs), Networks, FBLearner, Classification, Apache Cassandra, Sports, Software Architecture

Education

  • Master's Degree in Theoretical Physics (Quantum Field Theory)
    2019 - 2021
    Kyiv National University - Kyiv, Ukraine
  • Master's Degree in Computer Mathematics and Algebra
    2018 - 2020
    Kyiv National University - Kyiv, Ukraine
  • Bachelor's Degree in Computer Science and Applied Statistics
    2010 - 2014
    Kyiv National University - Kyiv, Ukraine

Certifications

  • AWS Solutions Architect Associate
    JANUARY 2023 - JANUARY 2026
    Amazon Web Services
  • AWS Certified Developer – Associate
    OCTOBER 2022 - OCTOBER 2025
    Amazon Web Services
  • Data Science: Data to Insights
    MAY 2017 - PRESENT
    MITProfessionalX DSx | edX
  • Artificial Intelligence (AI)
    JANUARY 2017 - PRESENT
    ColumbiaX CSMM.101x | edX
  • Second Place
    MAY 2011 - PRESENT
    ACM-ICPC, Country level
  • Bronze Medal
    JULY 2010 - PRESENT
    International Mathematical Olympiad (IMO)
  • Second Place
    MAY 2009 - PRESENT
    Kyiv International Physics Festival

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