Riola Fernandes

• Led the design and deployment of a Power BI dashboard for auditing outbound pallets, significantly improving visibility into store-level inventory discrepancies and generating $1.5M in annual savings for Target.
• Developed sophisticated trailer forecasting models using Time-Series and Regression analysis with SQL and Power BI, enhancing logistics efficiency and decision-making.
• Streamlined reporting processes in Hadoop, resulting in a 15% boost in forecast accuracy and facilitating more efficient data analysis.
• Collaborated with cross-functional teams to identify data-driven solutions, leveraging analytical skills to support strategic initiatives and improve operational performance.
• Engaged in continuous improvement efforts, utilizing data insights to drive process enhancements and optimize resource allocation.

• Led a cross-functional team of Data Analysts and Inventory Planners to integrate advanced statistical methodologies into vehicle and shipment planning processes.
• Achieved a 10% reduction in plan vs. actual variance, enhancing operational efficiency.
• Automated labor-intensive manual processes using Google Appscript, resulting in a 50% reduction in processing time and significantly improving data accuracy.
• Spearheaded the implementation of PowerBI dashboards for real-time monitoring of key performance indicators, facilitating data-driven decision-making.
• Fostered collaboration across teams to leverage data insights for strategic planning and operational improvements.

• Automated manual workflows by leveraging SQL queries from Apache Hadoop, enhancing efficiency through Python pandas in Jupyter Notebook.
• Achieved a remarkable reduction in analysis time, improving reporting SLA from 8 hours to just 15 minutes per week.
• Developed foundational metrics for the team by querying DB2, Teradata, and Hadoop databases, ensuring data integrity through thorough validation.
• Documented processes meticulously to facilitate knowledge sharing among team members, fostering a collaborative environment.
• As the inaugural member of the newly established team, took the initiative to lead collaborative efforts and drive project success.

• Developed web automation solutions using Python Selenium to efficiently download reporting tool data.
• Utilized pandas for data cleaning and analysis, enhancing data quality for decision-making.
• Automated the emailing process of the analyzed data to leadership using embedded Excel VBA within Python scripts for streamlined execution.
• Constructed a comprehensive Trailer Forecast Accuracy Report by identifying key performance metrics impacting trailer efficiency.
• Leveraged SQL Hadoop and Automation Portal to automate reporting processes, improving operational efficiency.
• Enhanced data visualization and analytics through PowerBI, facilitating better insights for stakeholders.
• Transitioning to a Senior Data Analyst role, focusing on advanced data analysis and IT integration strategies.

• Developed an interactive analysis dashboard leveraging PowerQuery and PowerPivot in MS Excel to analyze wage trends and their impact on labor costs.
• Engineered a robust forecasting model utilizing Regression and Time-Series analysis to predict future wage trends, enhancing data visualization and analytical insights for stakeholders.
• Spearheaded the PAN India wellness room initiative, successfully onboarding new vendors by conducting comprehensive market research to assess credibility and capability.
• Enhanced operational efficiency through data-driven decision-making, contributing to strategic planning and resource allocation within the organization.
• Fostered a culture of analytical thinking, empowering users with tools to interpret data trends effectively.

• Ensured seamless 24x7 operations for critical Siebel CRM, enhancing user experience and system reliability.
• Managed Incident Management processes, leveraging SQL to analyze and resolve issues efficiently.
• Conducted weekly data reconciliation between SAP and application databases, ensuring data integrity and accuracy.
• Collaborated with cross-functional teams to optimize support processes, driving operational excellence.
• Utilized data analysis skills to identify trends and improve incident response times, contributing to overall service quality.
• Developed documentation and reports to support data-driven decision-making and strategic initiatives.