Key Responsibilities:- API Development: I design, develop, and maintain two backend solutions for our product, ensuring high performance, scalability, and security.- AI Integration: I lead the integration of AI technologies into the product, leveraging machine learning and data analysis to enhance functionality and our user experience.- Data Science Expertise: I utilize my background in data science to inform development processes, optimize performance, and drive data-driven decision-making.

Some of the responsibilities that I had:- Analyzing large amounts of data to uncover patterns, trends, and insights that can inform product development and drive business growth.- Designing and conducting experiments to test hypotheses and evaluate the effectiveness of different strategies.- Creating automated processes that use machine learning and data analysis to improve efficiency and reduce costs.- Understanding the business domain and providing data-driven recommendations to the business teams.- Ensuring that data is accurate, consistent and compliant with the company's policies and regulations.

Some of the responsibilities that I had:- Designing, building, and maintaining data pipelines that collect, process, and store data from various sources such as web analytics, mobile apps, and e-commerce platforms.- Setting up and managing data storage systems such as data warehouses and data lakes to store and organize large amounts of data.- Implementing data quality checks and validation processes to ensure that data is accurate and reliable.- Creating visualizations and reports that allow business users to understand and gain insights from the data.- Documenting the data pipeline and data models for other team members and stakeholders to understand and maintain.

Some of the responsibilities that I had:- Collecting, storing, and analyzing data from various telecommunications networks such as cellular networks, internet service providers (ISPs), and satellite networks.- Designing, building, and maintaining data pipelines that collect, process, and store network data from various sources such as network devices, customer usage data, and network performance data.- Creating and integrating machine learning models in the family of natural language processing. Those models were specifically adapted to process customer services transcript between agents and customers.- Investigating and identifying the root causes of network issues and outages.- Identifying drivers behind negative customer experiences, call volume, churn, or loss of revenue.