Nino Mumladze, Data Scientist and Software Developer in Tbilisi, Georgia
Nino Mumladze

Data Scientist and Software Developer in Tbilisi, Georgia

Member since April 2, 2021
Nino is a software engineer with five years of industry experience in back-end development and, more recently, in data engineering internships at Amazon and Facebook. She has both theoretical and practical knowledge in cloud computing and distributed systems backed by a bachelor's degree in computer science. Nino will also complete a master's degree in data engineering and analytics from the Technical University of Munich in 2021.
Nino is now available for hire

Portfolio

  • Facebook
    Python, SQL, Data Visualization, Data Pipelines, Apache Hive, Apache Spark...
  • Amazon.com
    Python, Scala, Spark, Amazon Web Services (AWS), Linear Regression...
  • Experteer
    Ruby, RSpec, Docker, Docker Compose, GitLab, CI/CD Pipelines, iOS, Android...

Experience

Location

Tbilisi, Georgia

Availability

Part-time

Preferred Environment

MacOS, Ruby on Rails (RoR), Slack

The most amazing...

...thing I've developed is an Android messaging app that filters out incoming messages so that users aren't notified when they get annoying spams or ads.

Employment

  • Data Engineering Intern

    2020 - 2020
    Facebook
    • Designed, developed, and launched a new ETL and analytics framework for tracking detailed growth and retention metrics across ad infrastructure products.
    • Collaborated and communicated with cross-functional teams to create an accompanying dashboard to visualize metrics in a timely manner. The dashboard is used by team members and product managers to make data-driven decisions.
    • Presented findings and insights to the Facebook data engineering community to encourage wider adoption and build cross-functional collaboration.
    Technologies: Python, SQL, Data Visualization, Data Pipelines, Apache Hive, Apache Spark, ETL, Dashboards, Cloud Computing, Data Engineering, Data Analysis
  • Junior Research Scientist (Intern)

    2020 - 2020
    Amazon.com
    • Developed a robust and scalable package in Spark to perform statistical inference on large amounts of data.
    • Used Apache Spark's RDD layer to perform in-memory computations on a large amount of data in order to scale the package to work on millions of rows.
    • Implemented cloud technologies (AWS) to store the data (S3), perform computations on it (EC2), and distribute computations in clusters (EMR).
    Technologies: Python, Scala, Spark, Amazon Web Services (AWS), Linear Regression, Statistics, Optimization, Amazon S3 (AWS S3), Amazon EC2, AWS EMR, Cloud Computing, Machine Learning, Data Engineering, Data Analysis, Generative Adversarial Networks (GANs), Sentiment Analysis
  • Software Engineer

    2018 - 2020
    Experteer
    • Developed or fixed features for an online executive career service. Maintained iOS and Android mobile apps.
    • Tracked and fixed bugs using Jira as a reporting tool. Pushed code changes to the system, using GitLab with a CI/CD pipeline.
    • Incorporated third-party APIs for tracking user engagement and retention in Experteer's applications.
    Technologies: Ruby, RSpec, Docker, Docker Compose, GitLab, CI/CD Pipelines, iOS, Android, Mobile Apps, Jira, API Integration, Cloud Computing, Machine Learning, Back-end Development, Git, Google Cloud, Back-end, REST APIs, Ruby on Rails 5
  • Back-end Engineer

    2017 - 2018
    Vabaco
    • Developed and maintained parts of an application that provides a healthcare management system for the largest healthcare distributor in Georgia.
    • Updated the status of tasks and bugs I worked on, using Jira as a reporting tool.
    • Used Git as a source control system and kept clean documentation about the developing system for further assistance.
    Technologies: PostgreSQL, SQL, Postman, Healthcare, Jira, Git, Ruby on Rails (RoR), Ruby, Back-end Development, API Integration, Back-end, REST APIs, Ruby on Rails 5

Experience

  • Sentiment Analysis of Amazon Product Reviews

    Used natural language processing (with domain adaptation for unsupervised learning) to classify Amazon product reviews into positive or negative. The training data for one domain was used to train a classifier in another domain, using generative adversarial networks (GANs).

Skills

  • Languages

    SQL, Ruby, Python, Scala
  • Frameworks

    Ruby on Rails (RoR), Ruby on Rails 5, Spark, Apache Spark, AWS EMR
  • Storage

    Databases, PostgreSQL, Data Pipelines, Apache Hive, Amazon S3 (AWS S3), Google Cloud
  • Other

    Back-end Development, Informatics, Natural Language Processing (NLP), Linear Regression, Data Visualization, API Integration, Data Engineering, Data Analysis, Back-end, Information Theory, Computer Vision, Cloud Computing, Deep Learning, Machine Learning, Statistics, Optimization, CI/CD Pipelines, Dashboards, Mobile Apps, Sentiment Analysis, Generative Adversarial Networks (GANs)
  • Libraries/APIs

    NumPy, REST APIs, TensorFlow
  • Tools

    Postman, RSpec, Docker Compose, Git, Slack, GitLab, Jira, Apache Airflow
  • Platforms

    MacOS, Docker, Amazon Web Services (AWS), Amazon EC2, iOS, Android, Google Cloud Platform (GCP)
  • Paradigms

    ETL

Education

  • Progress Toward Master's Degree in Data Engineering and Analytics
    2018 - 2021
    Technical University of Munich - Munich, Germany
  • Bachelor's Degree in Computer Science
    2013 - 2018
    Free University of Tbilisi - Tbilisi, Georgia

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