Own the Pitstop squad's five outcome metrics: Launch Velocity, Handover Speed, Handover Accuracy, Pitstop Retention, and Indirect Cost per Parcel. Build the monitoring around them, investigate movement, and translate the numbers into next actions for the squad.
Run the analytics behind pitstop performance and pricing: which behaviours move handover speed, how commercial tiers and clawbacks are landing, which pitstops are systematically under
or over-performing, and what the in-app nudges are actually changing on the counter.
Quantify the impact of squad initiatives in cost terms: how much LiveOps load did this self-serve flow remove, how much Middle Mile driver time did this handover prompt unlock, and what is the CPP impact of retention work on mature pitstops.
Build launch readiness analytics: cohort ramp curves, time-to-maturity, where new pitstops break in week one, and how the launch playbook should evolve as volume grows.
Build the retention layer: a health score for pitstops, at-risk alerting, churn diagnosis triaged by cause, and the feedback loop back into acquisition and onboarding.
Investigate LiveOps ticket load by category and reason. Quantify what each ticket type costs, where the volume is concentrated, and which pillars should systematise it next.
Define KPIs and build dashboards that make Pitstop performance transparent to the squad, to operations, and to leadership.
Maintain and extend the squad's dbt models and data pipelines that underpin the monitoring layer.

At least 3 years experience, ideally with exposure to logistics, parcels, retail operations, or another network-scale operational business.
Fluent in SQL and experienced with BI tools, with strong problem-solving instincts.
Comfortable working alongside operations, design, engineering, and commercial stakeholders.
Can navigate messy operational data and turn it into metrics people trust.
Care about impact, not just insight. Success in this role is measured by whether the Pitstop network can scale without LiveOps scaling with it.
Communicate clearly with non-technical stakeholders and can explain what the data shows, where the limits are, and what to do next.

Equal opportunity employer committed to diversity, inclusion, and fostering a workplace where everyone thrives.

Data Analyst

Key skills