About me

Hi, I am Aisha, interested in all things data. I am particularly excited about using machine learning technologies in real world scenarios, making state of the art deep leaning models ‘actually useful’. Since my undergraduate thesis, I have been involved with NLP projects and did a couple of CV projects as well. I am thrilled how fast this field is growing and try to keep up-to-date with papers in NLP and sometimes CV. I am interested in learning to implement the entire ML project life cycle from data-pipelines to deployment and maintenance of an ML product.

Background

I finished by undergraduate in Computer Science and Engineering in 2019 and worked as a Machine Learning Engineer for almost a year before I joined Wikimedia Foundation as an Outreachy Intern (remote). I’ve been building data-pipelines, performing EDA and am moving towards applying gathered insights to create unified models and deliverable user-facing dashboards throughout the internship. My NLP journey started with my undergraduate thesis and I continue to mentor related research projects occasionally. I’ve used PyTorch, Keras, and Fastai for the most part to create my models and I’ve embraced HuggingFace to incorporate transformer architectures in my works. I’ve definitely been with SQL and APIs to create data pipelines. I extensively use pandas, numpy, matplotlib, seaborn and plotly for my EDA works. I am also learning SPARQL and getting deeper into big data handling. In my free time I develop my own web development project using the MERN stack and read books.

Goals

My long time goal is to keep learning and developing my skills to create end-to-end machine learning pipelines, lets be honest - learning never stops! I am looking for opportunities to work with data and ML related fields. I am a quick study and love to collaborate in teams. Being in Wikimedias open-source community has been an amazing experience and I’d love to continue working in such welcoming environments where everyone is supported! I am open to full-time or part-time data analyst, data scientist roles, remote or not. I believe I will bring new perspectives and diversification into teams and help maintain a welcoming culture.