About The Team
Support the
SPX Express Strategy Team in driving commercial performance by analyzing seller and sales data, monitoring key metrics, and executing projects that enhance acquisition, retention, and overall revenue impact. This role will transform commercial data into actionable insights, support strategic decision-making, and help design initiatives that strengthen seller growth and client relationships.
Job Description
Responsibilities:
- Analyze commercial performance data, including seller growth, sales productivity, and retention trends.
- Build and maintain reports and dashboards that track key commercial KPIs and surface performance issues.
- Monitor reports that provide insights for both seller acquisition and client retention.
- Lead and support ad-hoc projects and analyses that address overall business needs.
- Partner with Sales, Operations, and Strategy teams to design and implement initiatives that improve overall business performance.
- Conduct deep-dive analysis to identify performance gaps and recommend actionable solutions.
- Support end-to-end execution of strategic initiatives, from opportunity sizing to implementation and tracking.
- Develop tools and frameworks that enable commercial teams to make data-driven decisions.
- Present insights and recommendations to senior stakeholders to influence commercial strategy.
Requirements
Requirements:
- Bachelor's degree in Business, Industrial Engineering, Economics, Statistics, Computer Science, or related field
- 24 years of experience in business analysis, operations strategy, or process improvement roles in logistics, e-commerce, technology, or similar sectors (industry experience preferred but not required)
- Proficiency in SQL and Power BI is strongly preferred; candidates without prior experience should demonstrate readiness to learn quickly.
- Experience is sales performance analysis or revenue ops is highly preferred but not mandatory
- Intermediate to advanced Excel or Google Sheets skills for modeling, reporting, and data analysis.
- Ability to translate data into clear recommendations and operational improvements.
- Comfortable working with imperfect and large datasets in a fast-paced environment.
