Data Analyst for Supply Forecasting - Remote

Overview

This position involves developing analytical tools and reports using supply estimation data, harvest trends, and production assumptions for berries, aimed at supporting supply forecasting operations and contributing to Driscoll's mission of delighting berry consumers.

In Short

• Support the Supply Forecasting team by developing reports and maintaining systems.
• Collaborate with supply execution analysts to create and improve critical reports.
• Contribute to the continuous improvement of data collection and management processes.
• Interpret data and present preliminary findings using forecasting trends.
• Generate analysis to facilitate decision-making by integrating data from multiple sources.
• Design and maintain automated, scalable systems for reporting and dashboards.
• Produce critical reports and analyses on a daily, weekly, and monthly basis.
• Demonstrate analytical curiosity to identify data trends and propose potential uses.
• Conduct ad-hoc analyses under the direction of the Analytics Manager.
• Travel internationally and domestically as needed (approximately 5% of the time).

Requirements

• Bachelor's degree in data analytics, statistics, or agribusiness preferred.
• 2 years of experience in data analytics, preferably in the agribusiness sector.
• Excellent verbal and written communication skills; professional proficiency in English required.
• Ability to design and execute analytical projects independently.
• Understanding of business processes and key metrics relevance.
• Knowledge of Tableau or Power BI; proficiency in Microsoft Office, SQL, Python, and other BI and data visualization tools.
• Ability to address statistical problems, including data manipulation and statistical testing.
• Valid passport and unrestricted availability for international travel.

Benefits

• Opportunity to work with a global leader in the berry industry.
• Collaborative work environment across various departments.
• Engagement in continuous learning and professional development.
• Involvement in innovative data analysis projects.
• Flexible work arrangements with remote options.