Transform data into insights, equipped with practical knowledge of data collection, cleaning, transformation, analysis, and interpretation.
• Apply analytical skills in Microsoft Excel, SQL, Power BI, data vi…
Transform data into insights, equipped with practical knowledge of data collection, cleaning, transformation, analysis, and interpretation.
• Apply analytical skills in Microsoft Excel, SQL, Power BI, data visualization, dashboard development, and
reporting, with the ability to analyze datasets and communicate findings clearly to support business decisions.
• Deliver Data-Driven Solutions in working with structured datasets to identify trends, patterns, anomalies, and key
performance indicators (KPIs) while maintaining data accuracy and integrity.
• Demonstrate Analytical Achievement with hands-on data analytics projects through TS Academy, transforming raw
datasets into interactive dashboards and actionable insights that demonstrate problem-solving, attention to detail,
and data-driven decision-making.
<p>Managed hardware maintenance, basic troubleshooting, and routine updates for company computers to minimize downtime, enforce system reliability, and optimize operational performance.<br>
Cultivated and maintained strategic relationships with external suppliers and vendors to streamline procurement processes, resolve invoice discrepancies, and ensure timely inventory deliveries.<br>
Leveraged Microsoft Excel to organize operational metrics, monitor stock levels, analyze revenue trends, and produce comprehensive management reports.<br>
Prepared detailed financial summaries covering sales, total revenue, operating expenses, outstanding balances, and payroll, delivering actionable insights to support strategic leadership decisions.</p>
<p>Designed and deployed interactive Power BI dashboards tracking $15M+ in weekly transaction volumes, enabling executive leadership to monitor key performance indicators (KPIs) and operational revenue in real time.<br>
Wrote complex SQL queries, joins, and CTEs to extract and aggregate transaction records from PostgreSQL databases, reducing manual reporting generation time by 40%.<br>
Developed Python scripts (Pandas, NumPy) to automate weekly account reconciliation and fraud anomaly detection, cutting operational review times from 15 hours to under 2 hours per week.<br>
Cleaned and validated structured payment data across multiple legacy systems, resolving discrepancies to achieve a 98.5% data accuracy rate for monthly financial audits.</p>
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