Soomin Myung

Served as the sole data scientist to architect and deploy the organization’s first unified stock data foundation and integrated operational systems, establishing mission-critical capabilities that did not previously exist. Contributed to a £3.9M revenue uplift (£78M turnover company) and saved 5,200+ staff hours annually by institutionalizing governed, end-to-end systems; these replaced fragmented manual processes with accurate, data-driven operations and enabled proactive business planning and response. Data Foundation: Achieved 100% automation of stock data recording by engineering a unified platform that eliminated manual processes. Built a PySpark-Parquet ETL engine to ingest 6 years of 41M+ historical records, saving 140+ annual staff hours through a SQL agent scheduler.Forecasting: Designed a dual-scenario stock time-series forecasting framework (SARIMA vs. Momentum) to bypass distorted sales signals, enabling reliable item-level out-of-stock risk assessment tailored for 4-month import lead times.Unified Operational Layer: Architected a unified operational layer for 30+ cross-functional staff across purchasing, inventory, finance, retail, and logistics using SAP T-SQL and VBA, establishing a single source of truth that eliminated data discrepancies and enabled high-integrity reporting for C-suite decision-making.Anomaly Detection: Engineered anomaly-detection frameworks that identified systemic SAP COGS calculation failures and irregular membership-claim patterns (£700K) reviewed by the CEO/CFO.AI Automation: Designed an LLM-driven multi-agent purchasing workflow that integrates stock forecasting outputs and supplier & product history to generate structured analysis reports, internal purchasing request documents, and automated supplier-facing drafts, scaling consistent and context-aware decision-making, reducing the team's manual workload by 50% and saving 2,800 staff hours annually.

Python (PySpark), SAP Business One, Parquet, SQL, LLM (RAG/Multi-agent), Tableau, n8n, SARIMA, Excel VBA, Data Quality Management
Served as the sole data scientist to architect and deploy the organization’s first unified stock data foundation and integrated operational systems, establishing mission-critical capabilities that did not previously exist.
Contributed to a £3.9M revenue uplift (£78M turnover company) and saved 5,200+ staff hours annually by institutionalizing governed, end-to-end systems; these replaced fragmented manual processes with accurate, data-driven operations and enabled proactive business planning and response.
Achieved 100% automation of stock data recording by engineering a unified platform that eliminated manual processes.
Built a PySpark-Parquet ETL engine to ingest 6 years of 41M+ historical records, saving 140+ annual staff hours through a SQL agent scheduler.
Designed a dual-scenario stock time-series forecasting framework (SARIMA vs. Momentum) to bypass distorted sales signals, enabling reliable item-level out-of-stock risk assessment tailored for 4-month import lead times.
Architected a unified operational layer for 30+ cross-functional staff across purchasing, inventory, finance, retail, and logistics using SAP T-SQL and VBA, establishing a single source of truth that eliminated data discrepancies and enabled high-integrity reporting for C-suite decision-making.
Engineered anomaly-detection frameworks that identified systemic SAP COGS calculation failures and irregular membership-claim patterns (£700K) reviewed by the CEO/CFO.
Designed an LLM-driven multi-agent purchasing workflow that integrates stock forecasting outputs and supplier & product history to generate structured analysis reports, internal purchasing request documents, and automated supplier-facing drafts, scaling consistent and context-aware decision-making, reducing the team's manual workload by 50% and saving 2,800 staff hours annually.

Quantified the economic impact of a road-to-rail modal shift, estimating £350M–£600M in potential annual public sector savings by modelling reductions in transport externalities such as accidents, noise, and congestion.Developed a multi-factor weighting model to adapt European Commission’s transport cost standards to the Middle Eastern market, integrating socio-economic indicators including labour productivity, healthcare development, and population density.Synthesised diverse global datasets from the World Bank, Statista, and OECD to build a robust cost-benefit analysis for a large-scale infrastructure feasibility project.

Statistical Modelling, Data Synthesis, Cost-Benefit Analysis, Impact Quantification
Quantified the economic impact of a road-to-rail modal shift, estimating £350M–£600M in potential annual public sector savings by modelling reductions in transport externalities such as accidents, noise, and congestion.
Developed a multi-factor weighting model to adapt European Commission’s transport cost standards to the Middle Eastern market, integrating socio-economic indicators including labour productivity, healthcare development, and population density.
Synthesised diverse global datasets from the World Bank, Statista, and OECD to build a robust cost-benefit analysis for a large-scale infrastructure feasibility project.

ERP Data Management, Structured Reporting, Stakeholder Management, Data Quality ControlManaged ERP-based data governance for national energy R&D programmes, ensuring the integrity of project evaluation datasets used for government-level decision-making.Standardised complex evaluation reporting processes by synthesising fragmented project data into structured summaries, improving the consistency and transparency of review committee assessments.

ERP Data Management, Structured Reporting, Stakeholder Management, Data Quality Control
Managed ERP-based data governance for national energy R&D programmes, ensuring the integrity of project evaluation datasets used for government-level decision-making.
Standardised complex evaluation reporting processes by synthesising fragmented project data into structured summaries, improving the consistency and transparency of review committee assessments.

VBA Automation, Financial Data Analysis, Data Validation, ETL (Excel-based)Optimised financial data workflows by developing Excel-VBA tools to automate the extraction and validation of large-scale expenditure data from ERP systems.Streamlined financial reporting cycles, reducing manual errors and improving the reliability of budget planning through automated validation scripts.

VBA Automation, Financial Data Analysis, Data Validation, ETL (Excel-based)
Optimised financial data workflows by developing Excel-VBA tools to automate the extraction and validation of large-scale expenditure data from ERP systems.
Streamlined financial reporting cycles, reducing manual errors and improving the reliability of budget planning through automated validation scripts.