I am a PhD-qualified Data Scientist with more than 10 years of experience transforming complex, high-dimensional data into models, data products, and actionable decisions. My background combines biomedical research, statistical modelling, machine learning, and production analytics.
I currently work as a Senior ML Data Associate at Amazon AGI, where I evaluate generative AI and LLM outputs across multimodal data, including text, speech, images, and video. I focus on dialogue quality, factual accuracy, response ranking, data quality, and responsible AI practices.
I work across the full data lifecycle, from data ingestion, cleaning, validation, and experimental design through machine learning, visualisation, dashboard development, and stakeholder reporting. I am experienced in translating technical findings into practical recommendations for technical and non-technical audiences.
My core technical strengths are Python, R, SQL, machine learning, statistical analysis, data quality frameworks, and cloud-based data workflows. I have built interactive Dash and Plotly dashboards, clustering pipelines, automated tracking systems, and scalable analytical processes.
I am AWS certified in Cloud Practitioner and Machine Learning Engineering, and I have hands-on experience with generative AI evaluation, LLM fine-tuning workflows, prompt design, annotation governance, and root cause analysis. I value rigorous validation, reliable data, and responsible deployment of AI systems.
I also bring strong cross-functional collaboration and mentoring experience, having partnered with product, software, clinical, and research teams. I enjoy solving ambiguous data problems, improving operational workflows, and building robust solutions that support measurable business and scientific outcomes.