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Logistics Optimization Manager

Key Accountability Areas


BI, Data Visualization & AI-based Automations

  • Design, build, and maintain scalable dashboards and automated reporting pipelines covering fleet performance, delivery speed, order stacking, cost per delivery, and rider utilization
  • Own the end-to-end data lifecycle: from raw data extraction (SQL, BigQuery) through to business-ready visualizations (Tableau, Looker, Data Studio)
  • Automate recurring logistics reports to reduce manual data pulling and free leadership time for decision-making
  • Develop predictive models and forecasting tools for demand planning, supply crunch detection, and staffing efficiency
  • Translate complex, large-scale datasets into clear, actionable recommendations for logistics and operations stakeholders


Logistics Optimization and Utilization

  • Reduce delivery time across all stages: from order dispatch through to delivery, by identifying bottlenecks across the multiple DT sub-metrics
  • Collaborate with dispatching and algorithm teams to enhance order assignment logic and improve on-time delivery rates
  • Monitor and improve order stacking efficiency without compromising delivery SLAs
  • Track NPS and customer experience metrics tied to logistics performance, identifying drivers of dissatisfaction
  • Own analysis of logistics failures across vendor operations, rider operations, and customer touchpoints; recommend and execute fixes
  • Collaborate with workforce planning to optimise shift models, staffing levels, and on-demand-to-shift model transitions
  • Identify demand patterns and partner with growth and marketing teams to improve forecasting accuracy
  • Support rider hiring, onboarding, and payment process analysis to reduce attrition and improve supply reliability


Product Operations – Local & Global Rollouts

  • Act as the logistics liaison between local business stakeholders, local operations teams, and global product teams
  • Gather operational pain points, feature requests, and platform feedback; translate these into structured business cases for product prioritisation
  • Lead go-to-market (GTM) execution for new logistics initiatives: coordinating timelines, stakeholders, training materials, and deployment playbooks.
  • Support rollout and adoption of tools, ensuring operational readiness and post-launch performance tracking
  • Track rollout KPIs, adoption rates, and feedback loops, and present findings to product and logistics leadership


Logistics Issue Resolution & Stakeholder Support

  • Serve as the first escalation point for logistics issues: diagnosing root causes, mobilizing fixes, and communicating resolution timelines.
  • Manage performance during high-demand periods, including holidays, national days, and weekends, with proactive monitoring frameworks.
  • Coordinate with central/regional logistics and product teams (e.g. Delivery Hero central) to implement platform-wide improvements locally.
  • Minimize wastage per order through operational audits and targeted efficiency initiatives.
  • Provide training, change management support, and communications for stakeholder transitions tied to new logistics models or tools


QUALIFICATIONS/REQUIREMENTS


Knowledge and Experience

  • 5–8 years of experience in logistics analytics, operations, product operations, or a related field, preferably within food delivery, quick commerce, or a high-growth tech platform.
  • Proven track record in at least two of: BI/analytics delivery, logistics optimization, and product rollout execution.
  • Experience working in multi-market or global organizations with cross-functional, matrixed team structures.
  • Exposure to rider/fleet operations, last-mile delivery dynamics, and demand-supply management is strongly preferred
  • Exposure to A/B testing frameworks and statistical significance analysis in an operational context.
  • Advanced SQL proficiency, can write complex queries from scratch and independently pull your own data.
  • Strong experience with data visualization platforms: Tableau, Looker, Google Data Studio, or equivalent.
  • Comfortable with Python or R for automation, modeling, or data transformation.
  • Familiarity with project management and collaboration tools: Jira, Confluence, Notion, Asana


Education and Certifications

  • Bachelor's degree in Engineering, Supply Chain, Operations Management, Data Science, Computer Science, or a related quantitative field.
  • Master's degree in a relevant field is a plus

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