Software Developer in Fintech @ Citi Bank| Data Scientist
Education
MSci in Computer Science
Queen Mary University London
I completed an integrated Master's degree (MSci) which included both:
Bachelor's of Science
Master's of Science
I graduated with First Class Honours for both degrees.
Sep 2019 - July 2023
Experience
Software Engineer
Citi Bank
As a member of the Equity Finance team in the Markets Technology division, I am responsible for enhancing the backend of our platform. This includes performing integration testing and overseeing production releases to ensure smooth operations.
Sep 2023 - present
Software Engineering Summer Internship
Citi Bank
Developed a comprehensive JavaScript and Python application to manipulate and present data in a simplified format. Collaborated with the ICG Technology division for Risk in the bonds market to create an end-to-end solution.
Jun 2022 - Sep 2022
Coding Development Program
Google Get Ahead 2021 Program - Intern
Chosen by Google EMEA to join the invite-only virtual program designed to help develop technical skills. Coded weekly Leetcode-style coding challenges which involves various algorithms and data structures in Python.
July 2021 - Sep2021
Teacher Assistant
Queen Mary University of London
Teacher assistant of Dr Arman Rezaei Khouzani, Dr Anastasios Tombros and Dr Paul Curzon for the academic modules: Procedural Programming, Probability & Matrices, Computer Systems and Networks. I am helping students in their first and second year of study with understanding the concepts programming, software design and maths.
Sep 2020 - May 2023
Python Teacher
Algorithmics UK / BlueShift Education
I am teaching the basics of programming in Scratch, Python, Roblox to students aged eight to seventeen years old.
Mar 2020 - May 2023
Skills
Programming Languages & Tools
Key Strengths
Java, Python, JavaScript
Web Applications: React, XHTML, CSS, PHP, JavaScript
Deployment: CI/CD Pipelines: UDeploy, Jenkins, CLI for Linux
AI: Computer Vision, Machine Learning, NLP, Data Analysis, Deep Learning
Clubs & societies
Vice President
Google Developers Student Club (DSC) Queen Mary
As the Head of the Machine Learning project, I lead a team in building and developing
innovative solutions for local businesses and the community using Google's cutting-edge technologies.
We offer workshops on Machine Learning and TensorFlow to students from various disciplines,
empowering them with knowledge in one of the most transformative technologies of our time.
March 2020 - June 2021
Team Captain
Romanian National Team of Robotics ‘AutoVortex’
As the Team Captain of one of the three teams, I honed my critical thinking skills and deepened my knowledge of programming in Java and Python.
Working collaboratively, we faced and overcame various challenges, developing effective time management,
proactive problem-solving, and resilience under pressure while competing in international robotics competitions.
October 2017 - June 2019
Event Coordinator
Women in STEM Society @ Queen Mary University
Organized informative events for female students at our university, featuring guest speakers.
June 2021 - June 2022
Projects
Robotics ‘Hide & Seek’ project with Pepper the Robot
Explored technical aspects of implementing a hide-and-seek game with Pepper, a humanoid robot by SoftBank Robotics.
Developed advanced functionalities including:
Facial recognition
Human detection
Navigation (SLAM)
Designed and implemented movement behaviors to enhance human-robot interaction, ensuring a seamless and intuitive gaming experience.
Exploring Different Levels of Automation Inspired by Automotive Technology
for Surgical Robots: Advancing Autonomy in Surgical Robots
Research paper which focuses on empowering surgical excellence by unlocking the potential of autonomy in surgical robotics.
Aims to ease the burden of medical staff, reduce hospitalization costs, and minimize surgical errors to enhance patient safety.
Explores different levels of autonomy across fields to identify the best-suited levels for surgical robotics.
Highlights the current use of robotic surgery primarily for assistance tasks and the need to advance towards shared control and fully autonomous surgery.
Proposes the use of Artificial Intelligence to enhance robotic autonomy, enabling adaptable robots to make real-time decisions based on surgeon data.
Focuses on two specific types of tissue manipulation tasks, comparing three proposed algorithms against conventional manual surgery.
Emphasizes the potential for further automated applications to enhance autonomy in robotic surgery.
React Native-based app aimed to improve runners experience by giving clothing and
location suggestions based on the current weather while displaying accurate weather
forecast.
This is an ongoing team project for one of the undertaken modules.
App designed using Flutter which aims to connect individuals eager to help with local
charity organizations. The purpose of this software is to reduce the poverty level,
local hunger and increase awareness within our community. I used Cloud Firebase
for the database and Firebase Authentication for a strong user-based security.
React Native-based app designed to facilitate workforce reintegration through a mentoring program,
connecting users with industry specialists. Utilizing a matrix similarity algorithm, the software identifies
the top five mentor matches for mentees. This collaborative project showcases our expertise in software engineering.
The Mentor Filter
We implemented a filtering mechanism for FDM mentors. To ensure suitability, aspiring mentors are required to have a FDM recognised ID and submit an application. Technicians review the application and generate an account for authorized mentors, while declining unsuitable applications.
Matching Algorithm
The algorithm utilizes mentees' "areas of limitation" and mentors' "areas of expertise" to identify the top 5 mentors with the highest similarity rating. By converting these areas into vectors and performing similarity calculations, the system presents a list of the most suitable mentors for each mentee. In the provided clip, the system dynamically generates a list of mentors for a mentee who doesn't have an assigned mentor. The mentors are ranked from the most suitable to the least suitable.
Responsiveness of the app
The app's responsiveness was enhanced using Bootstrap and CSS, ensuring optimal display across various devices.
The clip demonstrates the seamless transition from desktop to mobile, showcasing adaptability to different screen sizes.
