AI Data Analyst with a strong academic background in Computer Science and Engineering. He has hands-on experience in deep learning for clinical image denoising and has worked on diverse projects including diabetes prediction and COVID-19 surveillance. He has held roles as a Python Backend Engineer and Java Software Engineer, with expertise in data analysis, predictive modelling, and API development. His technical skills encompass Python, Java, TensorFlow, PyTorch, SQL, and big data platforms, with proficiency in data visualisation and machine learning.
– Project Title: Preventing diabetes through behaviour
change: the impact of real-time food classification based
on post-meal glucose excursion (the Glook 3 trial)
– Data Analysis & Visualisation: Analysed users’ glucose
measurements and employed. Tableau to visualise data,
identifying key characteristics and patterns.
– Data Management: Utilised automated scripts to streamline
data cleaning and integration processes, ensuring accuracy
and efficiency.
– Predictive Modelling: Implemented deep learning models to
predict the impact of food consumption on users’ glucose
levels, contributing to the project’s core objective of
understanding and preventing diabetes through behavioural
change.
– Data Management: Led a multidisciplinary team in managing
customer data, utilising SQL on MySQL and big data
platforms Hive and Druid. Oversaw data cleaning and feature
engineering, driving improvements in the risk control
team’s decision-making processes.
– API Development: Engineered and deployed real-time APIs
with the Flask framework, leveraging the company’s in-house
machine-learning models. Achieved significant budget
reductions and boosted profitability.
– Automation & Efficiency: Pioneered the design of an
automated data acquisition system for the risk control
team, consistently processing 300k items daily. This
innovation resulted in substantial time and cost savings.
– Predictive Modelling: Formulated a credit fraud prediction
model using TensorFlow, enhancing the assessment of lender
reliability. The model was seamlessly integrated into core
business functions, improving operational efficiency.
– Public Health Tech Solution: Spearheaded the development of
a COVID-19 surveillance system using the robust Spring
framework. The system effectively visualised data for new
patients across all cities in China, serving as a pivotal
tool during the pandemic.
– Data Visualisation: Crafted user-friendly dashboards and
visualisations, ensuring health officials received swift
insights. This tool was instrumental in driving timely
public health decisions during a critical period.