𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 •Currently lead all BI analytics and reporting for the business using Infor BIRST, delivering insights across departments including supply chain, finance, and sales. •Work closely with process owners to map and understand data generation in Infor M3, identifying key database tables and fields to be ingested in the Data Lake and modelled in BIRST. •Manage the entire BI stack, including ETL processes, backups, and user access control to sensitive reports and information. •Successfully set up a pipeline to ingest historic data directly into the Data Lake, integrating it with live data from Infor M3 for continuous, seamless reporting across pre and post-go-live periods. •Playing a pivotal role in developing an interactive profitability model with the finance and sales teams. Involves understanding business profitability assessments and the finance and sales modules in Infor M3 to ensure the effective delivery of the model for informed product pricing decisions.𝐄𝐑𝐏 𝐂𝐨𝐧𝐟𝐢𝐠𝐮𝐫𝐚𝐭𝐢𝐨𝐧 & 𝐒𝐮𝐩𝐩𝐨𝐫𝐭 •Managed user setup and security in Infor M3, OS and Factory Track, providing ongoing support to process owners by debugging user administration issues. •Liaised with ERP core team to manage data migration from the legacy ERP system, ensuring accurate data cleansing and seamless transition to Infor M3. •Owned the Quality Control module, working with the technical team to create and configure specifications to meet business standards and automate the generation of Certificates of Analysis for export compliance. •Identified and resolved a critical supply chain issue related to order auto allocations that caused logistical bottlenecks. Developed a new process, trained production staff, and implemented a support hierarchy, reducing support requests and improving operational efficiency.

•Spearheaded the “Early Plant Disease Detection Project” , collaborating with the University of Essex,Innovate UK, and Wilkin & Sons Ltd. to drive project success and ensure effective implementation.•Developed and optimised power-efficient LoRa-based hardware for reliable, long-range transmission ofenvironmental data collected over a farm.•Implemented a robust plant imaging network using a Raspberry Pi as camera controller and localpre-processing/compression module for efficient cloud storage (AWS MySQL server).•Leveraged sensor and image data to achieve over 90% accuracy in predicting strawberry plant diseasesusing combined outputs of a Support Vector Machine and ResNet Based Convolutional NeuralNetwork.𝐈𝐄𝐄𝐄 𝐀𝐩𝐩𝐥𝐢𝐞𝐝 𝐒𝐞𝐧𝐬𝐢𝐧𝐠 𝐂𝐨𝐧𝐟𝐞𝐫𝐞𝐧𝐜𝐞 𝐏𝐮𝐛𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧: https://ieeexplore.ieee.org/document/10101121

•Successfully designed and deployed hardware with SAMD21 based IoT hardware for efficient remotedata collection and transmission over 4G (u-blox SARA-U201 LTE module).•Significantly reduced data costs by enabling local storage and pre-processing, cutting down cellulardata transmission.•Accelerated MVP release by implementing remote software updates for IoT nodes, ensuring up-to-datefunctionality and security.•Improved data aggregation using a Python Flask server with pandas and numpy for data cleansing andingestion into Google BigQuery.C / Python / Flask / Pandas / Numpy / Google BigQuery / IoT