I am a detail-oriented and results-driven Data Scientist with a passion for extracting meaningful insights from complex datasets. With 2.5+ years of proven experience, I have developed and implemented innovative problem-solving solutions to address business challenges. By leveraging cutting-edge statistics and machine learning techniques, I produce actionable recommendations that support well-informed decision-making.

My professional journey began at Sun Micronet, an award-winning computer software agency. As part of a diverse team of computer and network experts, I quickly established my niche in the data handling and network support environment. Within just a few months of starting as an intern, I co-managed over 20 software installation and data handling projects and became the youngest Computer Software & Network Support Manager in the company.

In this role, I worked closely with our largest client, a leading IT firm with a portfolio of over 15 developed software products. My tenure at Sun Micronet also provided opportunities to collaborate with several IT industry giants, further solidifying my expertise in data handling and network support.

While working at Sun Micronet for more than 1.5 years, I completed my undergraduate degree in Computer Application. I later pursued advanced education, enrolling in a Master’s programme in Data Science at Kingston University, one of the UK’s top universities. This globally ranked programme expanded my expertise in key areas such as machine learning, database and data management, applied data programming, data analytics, and visualisation.

During my Master’s programme, I held a part-time role as a Student Ambassador at getCredible, the first talent referral platform. This position honed my interpersonal and analytical skills as I introduced students to the app’s functionalities, provided detailed reports, and offered constructive feedback. My contributions enhanced the app’s user experience by identifying user preferences, pain points, and areas for improvement.

Since December 2024, I’ve been working as a Data Scientist at Fast Data Science, where I contribute to both technical development and open-source community engagement. I deployed a mental health LLM on Hugging Face, gaining early traction among clinical AI researchers. I improved our Drug Named Entity Recognition tool by integrating OMOP IDs, SMILES strings, and molecular weights for more accurate clinical NLP. I also manage our GitHub repositories, streamlining pull request workflows and reducing merge times by 25%. On Discord, I support our developer community by automating query handling and promoting coding challenges, improving engagement and response times while fostering an inclusive environment aligned with our mission.

Through my academic achievements and diverse professional roles, I have developed a robust foundation in data science, machine learning, and community engagement. My ability to balance technical expertise with interpersonal and organisational skills enables me to drive innovation, foster collaboration, and deliver impactful results.