نبذة عني
Senior Payments & Data Analyst with over 4 years of experience analysing operational, transaction, risk, and performance data within payments, fintech, and financial services environments. Holds an MSc in Big Data Analyt…
Senior Payments & Data Analyst with over 4 years of experience analysing operational, transaction, risk, and performance data within payments, fintech, and financial services environments. Holds an MSc in Big Data Analytics (Distinction) and is skilled in SQL, Python, Power BI, Snowflake, machine learning, statistical analysis, and data visualisation. Experienced in transforming large and complex datasets into actionable insights, developing dashboards, identifying trends, improving operational performance, and supporting data-driven decision-making.
الخبرة
Senior Payments & Data Analyst
<p>Analyse 300–400 payment exceptions and rejected transactions daily, identifying root causes, trends, and operational risk indicators across multiple acquiring partners.</p><p> Utilise SQL, Snowflake, Excel, and Power BI to extract, transform, analyse, and visualise transaction and operational data, supporting data-driven decision-making.</p><p> Identify recurring rejection patterns across payment providers including AMEX, Barclays, Elavon, and Fiserv, contributing to an approximately 65% reduction in transaction rejection rates.</p><p> Develop and maintain Power BI dashboards and KPI reports used to monitor transaction performance, exception volumes, backlog trends, settlement issues, and operational efficiency.</p><p> Conduct root-cause analysis on transaction failures, settlement discrepancies, and payment processing issues, providing actionable recommendations to stakeholders.</p><p> Perform ad-hoc data analysis and reporting to support operational decision-making, incident investigations, and process improvement initiatives.</p><p> Analyse large datasets to identify data quality issues, process bottlenecks, and automation opportunities, supporting continuous improvement initiatives.</p><p> Collaborate with cross-functional teams including Operations, SysOps, Onboarding, Implementations, and Merchant Support to resolve complex data and payment-related issues.</p><p> Perform QA and data validation reviews, ensuring accuracy, consistency, and compliance across payment investigations and operational reporting.</p>
Coaching Specialist (Performance Analytics)
<p>Analysed performance data for 15–60 frontline agents, tracking CSAT, quality, productivity, and adherence trends.</p><p> Developed automated Excel dashboards and KPI reporting frameworks using Pivot Tables, Power Query, and data visualisation techniques to identify performance trends and operational risks.</p><p> Prepared operational and performance reports using Looker, Salesforce, Zendesk, Excel, and PowerPoint.</p><p> Produced daily summaries and monthly reports with data-driven recommendations for team leads and senior stakeholders.</p><p> Supported training redesign and process improvement initiatives through performance analysis and quality insights.</p>
AML Analyst C9 (Financial Crime Risk Analytics)
<p>Investigated 10–20 transaction monitoring cases daily, analysing suspicious activity, sanctions exposure, and unusual payment behaviour.</p><p> Analysed customer transaction data, monitoring alerts, and risk indicators using SQL-based screening tools and Excel, identifying suspicious patterns and supporting compliance and risk assessment decisions.</p><p> Conducted CDD and EDD reviews for high-risk clients, supporting risk classification and compliance analysis.</p><p> Prepared analytical case reports for compliance officers and senior stakeholders.</p><p> Identified recurring alert drivers and supported improvements in monitoring procedures and data quality.</p>
Customer Service Representative
<p>Supported merchants with payment transaction queries, technical processing issues, and operational concerns.</p><p> Monitored transaction cases and maintained service quality through timely issue resolution.</p>
Customer Service Representative
<p>Supported customers with transaction-related queries, service requests, and client communication. Supported customers with transaction-related queries, service requests, and client communication.</p>
المشاريع
SELECTED DATA ANALYTICS & MACHINE LEARNING PROJECTS
<p>300,000 Customers – Credit Risk Analytics Using Machine Learning Analysed customer credit risk data and developed classification models using Logistic Regression, Random Forest, XGBoost, and Neural Networks. Engineered behavioural features and evaluated model performance using ROC-AUC and sensitivity-specificity trade-offs. 33 Years of Monthly Data – Energy Consumption Forecasting (Germany, 1990–2023) Analysed long-term energy consumption trends and developed time-series and econometric forecasting models using a rolling evaluation framework, achieving a MAPE of approximately 2%. 234,000 Patients – Healthcare Survival Analysis: Mortality Risk Modelling Analysed right-censored clinical data using Kaplan-Meier, Cox PH, frailty, and</p>