Aleron Eric Nunes Email & Phone Number

Phoenix, Arizona, United States

Berlin, Berlin, De

• As the lead project owner and key stakeholder for First Contact Resolution (FCR), defined metrics, set requirements, conducted sample analyses, and aligned with stakeholders. Developed a Tableau dashboard for monitoring and formed a collaborative task force across teams to improve FCR. These efforts resulted in a 5-point increase in FCR metric in 2023, enhancing customer experience and reducing costs by $1.7M• Took charge of chatbot reporting and transformed it to monitor chatbot performance, created a new metric as a key performance indicator (KPI) to accurately gauge chatbot capabilities• Proactively analyzed data and served as a strategic partner by providing recommendations and promptly addressing issues to mitigate their impact on KPIs. Identified areas for improvement in SOP’s and explored opportunities to streamline processes to create a better experience for agents and customers• Developed an ROI model for the team to implement a data-driven cost pricing strategy, which has been repurposed for other initiatives• Empowered stakeholders to self-serve by providing education on creating views and using filters in Tableau and Power BI dashboards• Participated in a hackathon and successfully developed a dashboard for tracking compensation strategies, while also mentoring a fellow employee during the process• Participated in company-wide projects and initiatives aimed at improving automation and workflow efficiency, such as the Shortship Compensation Process, LLM model for chatbot intent classification and metric alignment efforts• Completed the McKinsey & Company Leadership Essentials Program

Chicago, Il, Us

• Analyzed IRI and retail data using proprietary analytics tools to identify market patterns and trends• Enhanced shopper behavior insights by querying data with SQL to extract Basket Affinities & Penetration metrics• Worked closely with Category Managers to identify drivers of sales, monitored and measured KPI’s for various products to assist with strategies.• Analyzed location-based purchase trends to provide insights into consumer diets across the various stores.• Spearheaded quality checks and improved data accuracy, reducing error margin to 3% by cross-referencing multiple data sources• Reduced time for monthly deliverables by 1 week by creating automated reports for sales & marketing - Improved workflow efficiency by working with cross functional teams to identify appropriate data sources & centralize data pulls

Tempe, Az, Us

Developed Machine Learning models for Classification & Regression problems in R

Phoenix, Arizona, Us

Objective: To reduce marketing lead generation time and marketing costs by identifying and analyzing key drivers of marketing campaigns.• Reduced marketing lead generation time by 3 days and marketing costs by 25% by identifying and analyzing key drivers of marketing campaigns using Regression modeling and factor analysis in R• Extracted call center, campaign and customer data and performed data transformation and exploratory data analysis in R• Achieved a 10% increase in lead conversion rate by analyzing customer demographic data to optimize marketing qualified leads (MQLs)• Enhanced team efficiency by developing interactive PowerBI dashboards, providing actionable insights into the impact of call parameters (call time, duration, job function, customer title) on KPI’s• Reduced bizDev calling costs by 20% by performing optimization analysis in R, determining optimal call volume and timing for maximum efficiency

• Co-developed the SQL database with customer and product holding information• Increased workflow efficiency by creating data pipelines to support Power BI dashboards for financial decision and reporting• Recommended promotional strategies by developing sales bundles & provided time series sales forecast in Excel• Increased sales by 12% due to novel approaches to marketing and client acquisition by providing insights into seasonality trends and targeted marketing plans• Tracked monthly sales quota of employees to report whether targets were met

• Translate business propositions into quantitative queries and collect/clean the necessary data• Assisted data engineer in the design of ETL process• Created summary tables in Excel using pivots and helped the team analyze sales and income records to make better marketing decisions by drawing insights from the data

Master Of Science - Ms, Business Analytics

Bachelors Of Engineering, Electronics And Telecommunications