Data Analyst; Local

Description

This is an on-site position. The candidate must be local to the Pembroke, NH area or able to reasonably commute here.

• Excel in understanding complex systems, applying critical thinking in a technical environment, and adapting to dynamic team setting with a purposeful, creative, and analytical approach.
• Support sustainment and enhancement of existing data models.
• Develop data models and machine learning models.
• Execute and analyze established metrics and develop new metrics for both leadership visibility and programmatic performance.
• Contribute to data governance by maintaining accurate product dimensions, metadata and imagery in the planogram systems and database.
• Collaborate with business units to understand data requirements and translate into technical specifications for visual purposes by developing dashboards and reports using BI tools.
• Responsible for Ad Hoc analysis and reporting for senior leadership and stakeholders.
• Perform in-depth data analysis to identify trends and patterns for opportunities in process improvement.
• Performs other duties as assigned.

• Bachelor’s degree in Data Analysis, Computer Science, Statistics, or a related discipline (or equivalent combination of education and practical experience).
• 3–5 years of relevant experience in data analysis, reporting, or business intelligence preferred.
• A background in retail, supermarket operations, logistics, or warehouse settings—or a combination—is highly preferred.
• Strong critical thinking, problem-solving, and analytical skills.
• Ability to thrive in a dynamic, team-oriented environment.
• Knowledge of data governance principles, including accuracy, completeness, and maintenance of product-related data (imagery, dimensions, etc.).
• Experience using business data analytics platforms such as Salient, Nielsen, or similar.
• Proficiency with Microsoft Office Suite, particularly Excel.
• Strong SQL skills for querying and managing databases.
• Hands-on experience with business intelligence tools such as Power BI or similar platforms.

• Experience in cloud-based data platforms (Azure Synapse, Snowflake etc.)
• Background in statistical modeling, forecasting or machine learning.

• Work is normally performed in a typical office work environment.
• Limited physical effort required.
• Limited exposure to physical risk