Kitchener, Ontario, Canada
Experienced Software Engineer and Data Scientist with a demonstrated history of working in the computer software industry. Skilled in Python (and many of its data science libraries), SQL, Docker, and Linux Development. Deep experience in developing n-tiered, multi-containerized software systems. Strong engineering professional with a BS in Computer Science from IBA. Currently excitedly exploring and developing side projects in Go and Rust.
Applied AI Agent Engineering Team. Gemini Enterprise - CX Agent Studio. Using LLM agents to solve real-world problems. --- Previously: Cloud Healthcare Infrastructure: Tech Used: Bigtable, GCP, Golang, GoogleSQL, Python, Protobuf, Spanner Concepts used: API Compliance, Asynchronous execution, CI/CD, Cloud computing, data pipeline optimization, federated identities, horizontal and vertical autoscaling, long-running operations, message queues, quota management, Service Configuration, VPC Service Controls
Took a month off right after immigrating to Canada in March and then, around mid-April, I started practicing and applying for my first job here! I practiced hard on my skills in competitive programming and system design and eventually got my first job here as a software engineer. I also worked on some side projects and explored Ontario and adapted to the life here.
Designed and developed a highly modular synthetic data generator of various client environments for simulations of agent-caller pairings in call centers thereby significantly reducing hours of effort by the Algorithm Team on platform development _________________________ Worked on a data exploratory analysis application that AI Production team members use to monitor the production environment of call centers of Afiniti's clients and the effectiveness of predictive models. This application is able to handle clients having millions of rows of data with complex entities and is able to run anywhere Docker is present. Responsibilities: - Developed highly scalable and large-scale multi-container Docker applications and deployed them to various Linux-based call-center client environments - Researched and developed methods to represent data in each client generically in the context of Afiniti's proprietary agent-caller pairing models through MySQL and Python scripts - Set up and ran CI environments in Jenkins - Followed agile methodology; prioritized tasks into various sprints - Automated development and deployment process flows which included creating JIRA tickets ___________________________________________ Tech Used: Bash, Docker, Git, Grafana, InfluxDB, Jenkins, Linux, Markdown, MySQL, NodeJS, Python (Flask, NumPy, Pandas, SimPy, SQLAlchemy), RabbitMQ, React Concepts Applied: AI, Agile, Backend Development, CI/CD, Computer Networking, Database Systems, Machine Learning, Microservices, OOP, Probability & Statistics, REST, System Design, Web App Development
- Delivered value to clients such as Vodafone Hungary and Sky UK’s call centers by using predictive models that handle more than 11 million of its customers produced through data mining analysis via MySQL, SQL Server, Python and R - Wrote optimized queries and data management solutions in large databases with high volume data in MSSQL and MySQL - Created data management solutions in SQL for automation of production processes which process data from the client via queries and procedures to ensure effective performance of models - Adapted to changes in the client's data infrastructure by being involved in all aspects of the creation and evaluation of data models with ETL and BA teams - Gathered and documented the client’s requirements constantly and adapting the data management solutions to any changes promptly - Communicated effectively between internal teams and the client to ensure smoothness in client processes - Visualized, transformed and created reproducible reports of data via Python (Jupyter, NumPy, SciPy, Pandas, Matplotlib, Seaborn, Scikit-learn, SQLAlchemy, Dash) - Found patterns in data using Python and R to create predictive models which are deployed into the production environment where they generate revenue for the client and the company - Understood, implemented, optimized, and used various algorithms in Python and SQL to achieve high effectiveness of predictive models in production - Created interactive dashboards to present and explore data via Dash in Python - Took leadership of all AI Production related operations and making decisions appropriately - Trained new resources to accustom them to daily tasks Tech Used: Excel, Jupyter, Linux, Markdown, MySQL, Python (Dash, Jupyter, Matplotlib, NumPy, Pandas, scikit-learn, SciPy, Seaborn, SQLAlchemy), R, SQL Server, Talend Concepts Applied: AI, Agile, Data Mining, Database Systems, Data Visualization, Machine Learning, Probability & Statistics, Process Automation
- Performed data mining analysis on text data scraped from Twitter in the context of NLP in Python and displayed findings in Jupyter Notebook - Provided objective information on the effectiveness of installed cameras attached in certain locations concerning a reduction in crimes - Contributed to the development of an entity and sentiment-based searching data model for retrieval of various types of articles via various Python libraries - Contributed to a method for achieving Roman Urdu sentiment analysis of data from social media using Python, SpaCy, NLTK, Pandas, Matplotlib, Seaborn, etc.