SLA & Success Rate Tracking: Monitor and analyze key logistics metrics (Pick-up SLA, First Mile-to-Last Mile speed, and Delivery Success Rate) to identify underperforming seller segments.
Root Cause Analysis: Perform deep dives into Claim Leakage and High Loss/Damage cohorts to provide the Seller Management team with evidence-based talking points for seller consultations.
Segmentation Strategy: Develop data models to categorize sellers (e.g., High-Volume, At-Risk, or New) to allow for tailored support strategies.
Automation & Dashboard Development
Seller Health Dashboard: Build and maintain automated visualization tools (using SQL, Looker studio, or Appscript) that track real-time SPX performance and compensation trends.
Workflow Automation: Use low-code/no-code tools or scripts to automate routine tasks, such as weekly report generation for top-tier sellers or claim status notifications.
Alert Systems: Design automated triggers to alert the team when a high-value seller's logistics performance drops below a threshold.
Process Optimization & Simplification
Standard Operating Procedures (SOPs): Audit existing seller support workflows to remove bottlenecks, reducing the Time-to-Resolution for seller inquiries.
Feedback Loops: Create a systematic way to capture seller pain points regarding SPX and funnel them into the Product team for systemic long-term fixes.
Scalability Planning: Simplify the onboarding process for new sellers joining SPX to ensure a frictionless transition.
Cross-Functional Coordination
Ops & Product Bridge: Translate seller issues into technical requirements for the Product team to improve the Seller interface or logistics tracking features.
Stakeholder Management: Facilitate monthly performance reviews between Seller Management and Logistics Operations to align on capacity planning and improvement planning.
Requirements
Experience: 1+ years in Logistics, E-commerce Operations, or Business Intelligence.
Graduation: Bachelor's degree in Logistics, Supply Chain, Business Administration, or related field
Technical Skills: SQL, Excel, Google sheet, and experience with BI Tools (Google Data Studio). Python knowledge is a plus.
Mindset: A lean thinker who hates manual work and loves finding the shortest path to a solution.
Communication: Ability to explain complex data trends to non-technical stakeholders clearly.
