With over a decade of experience in technology, I have worked with with clients of all sizes and domains, from C-level to front-line, building scalable systems, implementing cutting-edge AI infrastructure, and architecting software for complex business domains.

My specialisms are in MLOps, productionising machine learning and AI systems, and Domain Driven Design, working with domain experts to translate the complexity of their business domains into efficient software architectures.

I work directly under our CTO to pivot the company technology strategy away from a Python and DBT approach to the automation of sustainability accounting.

I have collaborated with the research team to build a DSL written in Haskell, designed to encode Excel-based research theses in order to decrease error rates, speed up delivery times, and increase system observability.

Similarly, a large amount of research data stored in AWS S3 required the development of Rust tools to enable the research team to manage the data themselves without tech team intervention.

I also work with the design and strategy teams to build a Phoenix based Saas product in Elixir.

Co-Leading the ML-Infrastructure team: I am responsible for working with Data Science, Product Management, and the ML-Infrastructure team to productionise our machine learning capabilities. I manage the migration of our legacy embedded ML infrastructure to a Kubernetes-first microservice configuration, as well as the implementation of new features. I lead design sessions, co-ordinate with stakeholders, manage timelines, and contribute to implementation. I prioritise scalability, modularity, extensibility, and lowering the long-term maintenance burden with rigorous attention to software interfaces and data contracts.

Before co-leading ML-Infrastructure: Contributed to design and implementation of a microservice-oriented DDD refactoring of critical project models, collaborated developing an async client for remote system testing, tools for system observability on client deployments, and various reporting features.

Day to day, I am responsible for liasing with clients to collate requirements, designing and implementing new functionality in our proprietary ERP system, and maintaining the existing codebase. On occasion, I resolve infrastructure issues.

I managed (and worked on) the Barclays Bank integration project, liasing with Barclays and our client, and planning and executing the design implementation-test cycle.

I designed and implemented (with the team) a supplier management module, and a postal mail integration with ClickSend, among others.

I managed the implementation of a custom post-deal survey component in the company Salesforce instance.

I used pandas and the PyData stack to produce quarterly reports for the C-Level. I built a Flask web application to log and visualise my work, and generate reports for my manager.

I used the Python web-scraping tools to collect data on competitors, and pandas and PyData to combine it with deal information to produce heatmaps for regional sales targeting.

I built a Random Forest deal outcome model with a 60% accuracy rating.

Skills acquired: tenacity, thoroughness, determination, imperturbability, CRM system analysis and management, interpersonal and cross-cultural communication skills, market research, financial analysis, data research, priority management, client facing interaction, executive level discussions and presentations.; Business case analysis for system changes, responsible for successful execution of system changes, and error handling. Interdepartmental interface role, collating and prioritizing differing requirements in view of business orientation and goals. Handling organizational elements of regional and executive sales calls.; Volunteered at Misys, MEA, supporting GTM research, markets analysis and client prospecting for Misys Global Risk Management solution. Attended management meetings, strategy sessions, documenting findings and collaborating with various different functions in the organization.