Results-driven Data Scientist with experience in leveraging advanced analytics and modelling techniques to drive data-informed decision-making. Skilled at translating business requirements into technical solutions and collaborating with cross-functional teams to deliver high-value-added projects. Passionate about extracting actionable insights from diverse datasets and driving innovation through the implementation of cutting-edge data science technology.
– Data pre-processing and analytics skills such as data
cleaning, visualisation, and data modelling
– Applying machine learning techniques for quality
improvement in patient care and operations
– Leveraging Microsoft Azure for efficient data management
and analytics
– Contributing to evidence-based decision-making and
continuous quality improvement
– Ensuring regulatory compliance, particularly with HIPAA,
and supported reporting
– Collaborating seamlessly with healthcare professionals,
administrators, and IT teams
– Providing training on data tools and processes for
effective information utilisation
– Developed a precise multimodal AI chatbot for advanced
visual question-answering using scalable pre-trained
transformers. Integrate it into Tech Mahindra’s
architecture for optimal performance
– Collaborated with manager and team members to achieve daily
tasks promptly using agile
– Conducted a Google Scholar literature review for recent
papers to uncover advancements in machine learning
applications.
– Built CNNs and RNNs using Python with TensorFlow/Keras for
powerful image and sequential data analysis
– Implemented GitLab for comprehensive control: versioning,
collaboration, reproducibility, code management, reviews,
automation, tracking, documentation, and security.
– Developed and implemented flight data-driven solutions to
make the system more efficient.
– Performed tasks using R language for data pre-processing
and exploratory data analysis to make data-driven decisions
– Provided technical expertise to the information system team
in major application deployment by assisting in designing
processes to arrive at high-performance and optimal
operational solutions
– Evaluated various capabilities of machine learning
algorithms in modelling and architecture design techniques
– Suggested conclusions to support the line manager by
presenting insights gained from data analysis using
statistical tools.