Full-Stack Data Scientist & AI Engineer
Transforming complex data into strategic insights through advanced machine learning, full-stack development, and scalable cloud solutions. Passionate about solving real-world problems in sustainability, public health, and social impact through end-to-end data science.
With over 7 years of experience spanning Data Science, Machine Learning, Full-Stack Software Development, and Public Health, I specialise in building production-ready, cloud-native platforms that leverage advanced analytics and AI to drive strategic decision-making.
My expertise combines strong technical skills with research, business strategy, and consultancy experience. I'm passionate about creating AI-driven solutions that make a meaningful impact in sustainability, healthcare, and social good through comprehensive data engineering and full-stack development approaches.
Designed and deployed carbon footprint forecasting and lifecycle assessment tools using FastAPI, Streamlit, PostgreSQL/PostGIS, and React, supporting client decarbonisation roadmaps and environmental disclosures. Built predictive models with Prophet, XGBoost, and Linear Regression to simulate multi-scenario carbon projections and reduction targets. Delivered real-time water quality analytics by integrating sensor feeds into ArcGIS dashboards, enabling anomaly detection and spatial monitoring across 12 parameters.
Delivered custom ML solutions for fintech, logistics, and SaaS clients, including forecasting engines, deep learning frameworks using TensorFlow and PyTorch, NLP pipelines, and analytics dashboards. Built and deployed scalable cloud-native ML pipelines using AWS SageMaker, Lambda, GCP BigQuery, and Kafka, enabling real-time data ingestion, processing and analysis. Developed NLP tools using BERT and GPT-3.5 for text classification, sentiment analysis, and semantic search, improving predictive accuracy by 25%.
Built time-series forecasting models (Prophet, ARIMA, XGBoost) for public health and NGO clients to support demand prediction, outreach planning, and funding allocation. Designed and deployed ETL pipelines using Apache Airflow, SQL, and Python, integrating large-scale ODK and XLS survey data into cloud data lakes. Applied machine learning algorithms using Python, TensorFlow, and PyTorch to develop predictive models for healthcare interventions, achieving a 20% improvement in prediction accuracy.
Started with data collection and audio transcription, progressing to data wrangling and ETL processes using SQL to preprocess and transform data, automating data cleaning tasks with VBA in Excel, which reduced manual errors by 30%. Developed and deployed Power BI dashboards using DAX for advanced calculations, enabling real-time data visualisation. Advanced to data analysis using Python and SQL for statistical analysis and predictive modelling, uncovering trends that led to a 30% improvement in health interventions and outcomes.
AI-powered mental health platform using deep learning for emotion detection and cognitive state analysis from brainwave data.
Enterprise platform for forecasting GHG emissions using activity data and AI models with scenario simulations and accuracy scoring.
Computer vision and ML-based skin analysis system providing personalised skincare recommendations through image recognition algorithms.
AI-powered career platform with CV/cover letter generation, job matching algorithms, and productivity tracking for job seekers.
AI-powered knowledge management tool for intelligent document querying and organizational knowledge search with semantic analysis.
Real-time earthquake monitoring and analysis dashboard using global datasets with interactive maps and geospatial tools.
Cognitive Computation and Systems Journal
This study presents a novel approach to combining emotional distress detection with automated psychological support, utilising deep learning models to improve mental health interventions. The research demonstrates the integration of BERT-based emotion detection with GPT-powered conversational AI for providing psychological first aid.
End-to-end AI solution development including deep learning models, NLP systems, computer vision applications, and recommendation engines. From research to production deployment with strategic AI consulting and implementation guidance.
Complete web and mobile application development using modern frameworks and technologies. From frontend interfaces to backend APIs and database design.
Complete data science solutions from data collection to interactive dashboards. Combining statistical analysis, predictive modelling, and modern web development.
Scalable data infrastructure using modern technologies like Spark, Kafka, and Hadoop. ETL pipeline development and big data processing solutions.
Specialised environmental and sustainability consulting including carbon footprint analysis, lifecycle assessments, climate change impact studies, and environmental monitoring solutions.
Healthcare and public health analytics including epidemiological modelling, health intervention evaluation, and population health insights.
Ready to collaborate on your next AI, data science, or full-stack development project? Let's discuss how we can create impactful solutions together.