Remote Warehouse Data Analyst
- sunderland, tyne and wear, SR1 1AA, United Kingdom
- Remote
- Full time
- £40,000 - £40,000 Per Annum
Job Description
About the Role
Our client is seeking a highly analytical and technically skilled Remote Warehouse Data Analyst to join their global logistics team. This role focuses on leveraging data to drive improvements in warehouse efficiency, inventory management, and overall supply chain performance. You will be responsible for collecting, analyzing, and interpreting large datasets to identify trends, pinpoint bottlenecks, and provide actionable insights that inform strategic decision-making, all within a fully remote operational framework.
Key Responsibilities
- Collect, clean, and analyze data from various warehouse management systems and logistics platforms.
- Develop dashboards and reports to visualize key performance indicators (KPIs) related to warehouse operations, inventory accuracy, and throughput.
- Identify trends, patterns, and anomalies in operational data to uncover opportunities for process improvement.
- Collaborate with warehouse managers and operational teams to understand their data needs and provide relevant insights.
- Develop and maintain predictive models for forecasting demand and optimizing inventory levels.
- Present findings and recommendations to stakeholders in a clear and concise manner.
Requirements
- Proven experience as a Data Analyst or in a similar analytical role, preferably within logistics or supply chain.
- Strong proficiency in SQL, Excel, and data visualization tools (e.g., Tableau, Power BI).
- Experience with statistical analysis and modeling techniques.
- Excellent problem-solving skills and a keen eye for detail.
- Ability to work independently and manage projects effectively in a remote setting.
- Strong written and verbal communication skills for remote collaboration.
Benefits
- Competitive salary and potential for bonuses.
- Fully remote working position offering significant flexibility.
- Access to cutting-edge data analytics tools and technologies.
- Opportunities for professional development and upskilling in data science.
- Be part of a forward-thinking, data-driven logistics organization.


