Sales Data Analyst

The Sales Data Analyst is responsible for collecting, analyzing, and interpreting sales data to support the decision-making process within the organization. They play a critical role in identifying sales trends, optimizing sales strategies, and forecasting future performance to drive revenue growth. Duties and Responsibilities Data Forecasting Produce accurate sales forecasts based on historical data, trends, and predictive modeling. Aid sales and marketing managers in item level forecasting by understanding each retailer’s performance and seasonality. Ensure that sales data is up-to-date, accurate, and free from errors or inconsistencies in databases and systems. Data Analysis, Reporting, and Visualization Provide precise and correct data analysis, reports, and insights with less than 1% error rate in monthly reports. Efficiently process large datasets using appropriate tools and automation such as Excel, Power BI, Tableau, SQL, or Python to minimize manual work of data analysis and reporting. Provide general sales reporting and analysis that assists in monitoring sales and revenue performance for all brands. Provide analytical support for internal and external presentations including presentations for the brand managers, sales, and trade marketing. Create charts, graphs, and data visualizations for stakeholders and ensure that visuals are clear, readable and relevant. Delivery of Actionable Insights

Help derive and translate strategic insights from different sources of data available and present to cross-functional teams at all levels

Translate raw sales data into actionable insights that drive sales growth, improve processes, or enhance decision-making. Assists in the identification and development of business opportunities through analysis and interpretation of consumer, customer and market data

Ensure accurate reports, insights, and dashboards are produced within the agreed-upon timeframes. Sales Funnel Optimization

Contribute to optimizing the sales funnel by providing data-driven insights into each stage of the sales process. Demonstrate improvement in sales conversion rates or reduction in sales cycle time. Must give data-driven recommendations that will contribute to sales growth or operational improvements. Training and Knowledge Sharing

Train sales and marketing teams on using data, reports, and dashboards effectively. Commitment to staying updated on industry trends, new analytical techniques, and software/tools to improve data analysis.