Nino Mumladze, Developer in London, United Kingdom
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Nino Mumladze

Verified Expert  in Engineering

Data Scientist and Software Developer

London, United Kingdom

Toptal member since April 2, 2021

Bio

Nino is a software engineer with a proven record of industry experience in back-end development and data engineering with companies like Amazon and Meta. 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.

Portfolio

Meta
Python 3, SQL, Visualization, Data Analytics
Facebook
Python, SQL, Data Visualization, Data Pipelines, Apache Hive, Apache Spark, ETL...
Amazon.com
Python, Scala, Spark, Amazon Web Services (AWS), Linear Regression, Statistics...

Experience

  • Ruby on Rails (RoR) - 4 years
  • Back-end Development - 4 years
  • Ruby - 4 years
  • Python - 4 years
  • Cloud Computing - 2 years
  • Machine Learning - 2 years
  • Data Analysis - 2 years
  • Data Engineering - 2 years

Availability

Full-time

Preferred Environment

MacOS, Ruby on Rails (RoR), Slack, Python, SQL, Google Cloud

The most amazing...

...environment I've worked in is full of people who know how to work as leaders and team members.

Work Experience

Data Engineer

2021 - 2025
Meta
  • Worked on monitoring the correctness of the experimentation platform for ads delivery systems at Meta, operationalizing metrics that measure the reliability of the platform, as well as best practices when it comes to setting up an experiment.
  • Ensured the power of the experiments was adequate by deploying a power calculator to set up experiments that deliver statistically significant results.
  • Worked on Reality Labs products such as workrooms (an app for meetings in virtual reality) and Ray Ban Meta processing pipelines (NLP).
Technologies: Python 3, SQL, Visualization, Data Analytics

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, Amazon Elastic MapReduce (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, 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).

Education

2018 - 2021

Progress Toward Master's Degree in Data Engineering and Analytics

Technical University of Munich - Munich, Germany

2013 - 2018

Bachelor's Degree in Computer Science

Free University of Tbilisi - Tbilisi, Georgia

Skills

Libraries/APIs

NumPy, REST APIs, TensorFlow

Tools

Postman, RSpec, Docker Compose, Git, Slack, GitLab, Amazon Elastic MapReduce (EMR), Jira, Apache Airflow

Languages

SQL, Ruby, Python, Scala, Python 3

Frameworks

Ruby on Rails (RoR), Ruby on Rails 5, Spark, Apache Spark

Storage

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

Platforms

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

Paradigms

ETL

Other

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

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