Key responsibilities

• Creating (from inception to deployment and maintenance) a ChatGPT-based, end-to-end service for updating product pages on Amazon Marketplace.

  • Using dynamic prompt engineering and NLP based post-processing, the product automatically re-writes various sections of the product page, to include SEO keywords and phrases.​

  • Improves the search-engine results page placement of the products, immediately resulting in increased sales.

  • Maintains a natural-sounding title, bullet points and description to remain appealing to the customer/reader.

  • Everything achieved in one round of prompting. No dialogue/intervention required for a fully automated service.

  • Successful in both English and German (a market niche).

  • New service resulted in dozens of new customer trials and signings.

  • Python, PostgreSQL, Dramatiq (async), FastAPI

• Maintaining the data warehouse in GCP Big Query

  • ​Terabytes of data processed weekly comprising Amazon Seller statistics and financial data ​

Key responsibilities

• Modelling, organising and storing all company data (GCP Datastore, GCP BigQuery,  GCP Cloud Storage, Kafka event logs, memcached lookup keys)

• Collection and curation of publicly available data, and their transformation into data products and actionable business intelligence to add value for the enterprise and stakeholders (Python scrapy, headless browsers, ElasticSearch, JanusGraph - Gremlin)

• Ideating and evaluating machine learning driven features to improve the customer journey/experience to maximise customer engagement (open source and GCP BiqQuery ML)

• Building a team of data professionals and fostering their understanding of the company and data strategy (hiring two data science graduates and a data engineering intern)

• Establishing and maintaining the data policy and governance (PII segregation and anonymization)

• Staying on top of latest trends in data mining and machine learning and identify emerging opportunities for commercial advantage (e.g. integrate ChatGPT into search)

Milestone achievements:

• Development of ML models to predict specific app user behaviours

• Automation of ML pipeline (parameter optimisation and evaluation/comparison of multiple models), and versioning repository for models and preprocessing modules

• Schema design and data model to support microservices architecture and lightweight, non-intrusive partner integration

• Data ingest framework from our GCP DataStore model to JanusGraph

• Automated document reader, with open source passport AI library and python multi-processing

• Code re-use evangelist – moving boiler plate logging, data access and processing code to standard modules and Docker containers

• Combining BQ and GA into KPI’s, management info, and engagement analytic dashboards in Looker (previously GCP Data Studio)

• Automated updates of our catalogue of international degree courses

• Custom Full-text search indices for end users, pattern matching and partner integration

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In the R&D and PoC pipelines:

• Automated, completely customisable, operational targets and KPI’s based on customer engagement and digital journey data for a multi-tenanted application.

• Short text cleansing; a process for cleaning up snippets and captions from externally sourced text using (n-grams and word-embeddings, best regex discovery using grammatical evolution)

• LDA Similarity and/or graph-based search engine enhancement (currently using ElasticSearch full-text indexing capabilities)

• Web-page and document content classification and tagging

• Social graph to track faculty and research contributions, determining which universities have prestige and social capital in a particular discipline

Full-time research to PhD in XAI (eXplainable Artificial Intelligence), a branch Machine Learning concerned with interpretable models and explanations of black box algorithms for fair and transparent automated decision making, and actionable insights.

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Published three peer-reviewed articles in prestigious academic journals:

• CHIRPS: Explaining Random Forest Classification

• Ada-WHIPS: Explaining AdaBoost Classification with Applications in the Health Sciences

• gbt-HIPS: Explaining Gradient Boosted Trees Classification

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Developed expertise in the following areas:

• Training and testing a variety of explainable and black box ML models (SHAP, LIME, XGBoost, RandomForest).

• Automation of complete ML pipeline from pre-processing through parameter optimisation, and evaluation.

• Generating flexible, dynamic, high-quality graphical results in Python (matplotlib, seaborn), R (ggplot, lattice and base graphics), and LaTeX (tikz).

• Communication and public speaking, delivering seminars and lectures expound my research to various audiences.

• Research skills - reviewing complex academic literature to find gaps and opportunities.

• Designing and executing experiments to test potential solutions and assess the results using suitable metrics and statistics.

• Demonstrating complete autonomy, intrinsic motivation, and tenacity by finishing the final year of research and viva preparation in the height of the COVID-19 pandemic when access to my supervisors and peers was drastically limited.

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I gained exposure to the following topics via peers' and supervisors' research:

• Stream analytics

• Extreme pruning and lightweight models for IoT

• Population-based search and optimisation (meta-heuristics, genetic algorithms)

• NLP and Word Embeddings

Delivery of the practice-led activities for students of MSc in Enterprise Systems Management and BSc Business Information Systems. I covered topics related to enterprise scale Business Intelligence and Data Warehousing, foundational statistics, and data visualisation.

I redesigned and updated the course content to meet the university's employability objectives:

• Updating the course materials from SAP Business Warehouse 7.3 to SAP BW on HANA (7.4)

• Communicating the benefits of column-oriented data storage

• Demonstrating the value to the enterprise of self-service BI tools such as SAP Lumira and Tableau

• Providing students with an introduction to predictive analytics and forecasting

• Presenting an overview of project management of BI systems implementation

• Sharing the skills needed to communicate data-driven insights to non-technical users

I also designed and delivered "Visualising Categorical Data," a statistics seminar / workshop with hands-on R exercises based on the book of the same name by Michael Friendly et al.

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This work helped to subsidise my income during my PhD research.

I set up a limited company to work on a small number of projects with select clients, to subsidise my income during my PhD research.

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Deliverables included building data wrangling pipelines in Alteryx, training/evaluating predictive models in AWSML, and creating BI dashboards in Tableau for a client in London.

MSc in Business Intelligence at BCU was the only Business Intelligence course that combined the major topic with modules in key areas of interest to me:

• Technology entrepreneurship

• Advanced applied statistics

• Data mining/machine learning

I scored 97% for my Master's dissertation "A novel, association rules-based algorithm for imputing missing data in Likert scales", which involved a complex student survey data set and demonstrated my keen interest in advanced data analysis.

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Aside from the academic studies, I also gained exposure to Oracle, SAS and Qlik technologies.

I worked freelance on limited projects with select clients, to subsidise my income during my Master's degree.

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• Developing machine learning models to predict various student milestones (Generalised Linear Models, Logistic Regression Models, Survival Models, Multi-state Life-cycle Models, Process Mining). These allowed the client organisation in Singapore to develop an intervention strategy for potentially failing students.

• Designing and delivering training to two newly recruited/promoted programme directors on Agile delivery of Project/Programme/Portfolio Management, and value/benefit realisation for a client in Sydney, Australia

Working on a pro-bono (unpaid, volunteer) basis, I helped B-Change to clarify and focus the strategy and positioning for their mobile app. I designed and facilitated a two personalised, creative brainstorming and innovation sessions in Singapore and Sydney.

I relocated to Singapore to set up a greenfield Technical Business Analysis function to support business critical, digital transformation. In Singapore's highly regulated private education sector, it is a hygiene factor to demonstrate a commitment to raising standards through business process improvement, quality assurance and monitoring. Failure to do so results in fines and loss of accreditation.

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I set the standard for future expectations of the role, defined and delivered projects that brought value to the business, driving operational excellence through the development of business insights and proposing business process improvements. The role became an integral part of the business's modus operandi when conducting new business and digital transformation projects.

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I used R programming, techniques of process mining (ProM, Fluxicon Disco), Business Intelligence tools (Tableau and OLAP databases/data warehouse), and specialised statistics of categorical/count data to find operational efficiencies and examples of process non-conformance.

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I also drove the benefits realisation programme; working with C-level and SMT stakeholders to identify the expected post-delivery benefits of each project, in order to demonstrate the benefit to the bottom line.
 

Responsibilities:

• Develop the new BA function and communicate the ongoing value-add to the senior management team and the compliance department

• Design and document new processes and grow the function's reach over multiple departments

• Analyse processes and re-engineer them to meet business objectives (ex: improve student experience and optimise resource utilisation)

• Lead and project manage process/system change initiatives

• Identify performance trends, conduct sales / financial / operational data analysis, interpret results and develop business insights

• Build and work with matrix and cross functional teams across the company

• Stakeholder engagement and communication strategy

Note, this was a short secondment to Singapore sandwiched into my tenure as Programme Director at KIC.

Following a resignation by the incumbent IT Director in our Singapore division, I stood in  until the selected permanent replacement was able to commence his new tenure. I took responsibility for continuity of a number of business critical and transformative projects. and liaised regularly with the executive board.

In a short time, I was able to introduce the existing team to the Agile/Kanban framework to improve visibility and transparency of the IT development processes. I facilitated, coached and mentored the existing team, providing full support for their HR needs (e.g. review training and development plans, succession plans, retention and risks etc).

Responsible for the defining and delivering a coherent portfolio of projects and programmes aligned with the organisation's strategic objectives. 

• Worked with the CEO to create project portfolio aligned to her strategic objectives.

• Created a benefits realisation plan to see projects through beyond delivery, ensuring that projected efficiencies and capabilities were fully realised and tracked to the bottom line.

• Identified key stakeholders within the business to act as project sponsors, to help evangelise the benefits of each programme and drive their adoption throughout the business.

• Communicated technical concepts to non-technical users in plain English.

• Introduced the SMT to a variety of techniques for planning and executing strategic change (Scrum and Kanban, Balanced Scorecard, Portfolio & Programme Management, Innovation Games, Sketching at Work, Systems Thinking, Design Thinking, Business Model Canvas).