● Led productionising a large-scale data science solution, implementing automated pipelines, data cleaning, and batch processing using SQL, Spark, Python, Airflow, Azure DevOps CI/CD, and Docker. Optimised queries to reduce processing time nearly by 50%, handling millions of records per job. Collaborated across multiple teams, assessing resources, preparing timelines for delivering a pipeline surfacing insights to public and government stakeholders. ● As the lead Data Scientist (AI/ML Engineer) of an Energy organisation, built relationships across the organisation and discovered opportunities to establish value propositions and demonstrate use cases (4 in 4 months) leveraging Gen AI, RAG and ML to uplift data quality and operational efficiency. ● Conducted market segment analysis consisting of 70k+ customers across 5+ segments, examining consumer behaviours in response to external factors such as weather and socio-economics, clustering these segments to identify heterogeneity within homogeneous groups to determine root causes delivering consumer profiles for better customer engagement. ● Involved in the negotiations with different technology vendors and stakeholders to bring data science cloud platforms into the organisation, acting as a bridge between business strategy teams and technical teams.

● Represented the organisation in risk and compliance space as an AI expert and collaborating with internal teams of 2 of the Big4 banks in Australia in the diagnostics operations of 7 weeks when getting them onboard. ● Led and developed a conversational chat application and an alert generation method catered for finance from MVP to production leveraging Gen AI, AI Agents, LLMs, LangChain, Azure AI, RAG, Fast API, CI/CD and proprietary knowledge sources. ● Restructured and modularised a legacy NLP Fin-tech ML clustering model for financial risks, developed evaluation methods, and enhanced clustering quality by 32%.

● Developed a suite of deep learning and statistical models including feature engineering, model training, evaluating and finetuning in collaboration with the Defence Science and Technology Group (DSTG) for Encrypted Traffic Analysis to secure IoT devices against privacy threats from 15+ manufacturers including Apple, Google and Amazon. ● Communicated project outcomes using visualisations to a diverse set of stakeholders, including industry partners, and academics to help them better understand the results of the project and make informed decisions. ● Supervised and mentored 2 junior team members and closely worked with them during the processes of data collection, data wrangling and labelling, model development and publishing.

● Designed and implemented software tools to ensure integrity of the SQL databases of Sydney WestConnex ITS project, which involved managing 3000+ devices such as traffic cameras, fire alarms, and variable speed signs. ● Solely managed cross-functional weekly software builds, deployments and DevOps of the entire project that included deployments in 3 development servers, 3 test servers, and 6+ client workstations utilising CI/CD tools such as Jenkins, Ansible and Git. ● Conducted robot regression tests and functional tests for 11+ functional packages, such as fire detection, ventilation, and reporting, ensuring the quality of customer deliverables for each build.

● Implemented a statistical analysis and developed machine learning algorithms to identify traffic movement patterns in Sydney using Wi-Fi hotspot (160+) data to enhance TfNSW's ability to optimise transportation strategies. ● Developed algorithms and data-driven models using traffic physics to detect anomalous data that reported above 94% accuracy in high density Sydney M4 vehicular network. ● Led and core developer for prototype development of a deep learning-based traffic monitoring system deployed and tested over 2500+ vehicles at 2 different locations in Sydney. ● Led and developed an in-app secure payment enabled Mobility as a Service mobile app with 5 team members from 2 different countries. ● Configured open source (SUMO from German Aerospace Engineering) and commercial traffic micro-simulators (VISSIM and Aimsun), network simulators (Omnet++), and data analytics tools. ● Demonstrated and tutored over 4 different transport data analytics courses.

● Developed core Project Management functionality of IFS ERP software solution used by 2000+ customers in over 60 countries. ● A key player in the product support team involved in bug corrections, task investigations, working alongside with customers, and providing functional feedback to run their operations smoothly.

● Developed a real-time multi-monitor desktop capturing and remote streaming tool across 6+ development teams using C# socket programming and WPF as a training tool for the US military. ● Involved in video and audio encoding using C++ and software libraries including OpenCV, live55 and ffmpeg.