Data Analyst - Pitstops

About the role

You will own the analytical layer that measures how the Pitstop network operates on a daily basis. You will translate messy, behaviour-driven operations into clear metrics that the squad can act on. You will investigate why handover speed varies, why some pitstops churn, and how in-app nudges change what happens on the counter. You will own the monitoring that lets the same team manage twelve times as many pitstops without adding people. You will sit at the intersection of operations, product, and data, turning real-world friction into measurable experiments. You will be the squad's source of truth for what is working, what is breaking, and where to intervene next. You will work closely with operators, engineers, and retailers to design systems that make the right behaviour the easy behaviour. You will maintain the dbt models and dashboards that keep every stakeholder aligned on the same numbers.

Key facts

What you'll do

• Own the Pitstop squad's five outcome metrics: Launch Velocity, Handover Speed, Handover Accuracy, Pitstop Retention, and Indirect Cost per Parcel, building the monitoring around them, investigating movement, and translating the numbers into next actions for the squad.
• Run the analytics behind pitstop performance and pricing, examining 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, measuring how much LiveOps load each self-serve flow removes, how much Middle Mile driver time each handover prompt unlocks, and what the CPP impact of retention work is on mature pitstops.
• Build launch readiness analytics, including 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, creating 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, quantifying what each ticket type costs, where the volume is concentrated, and which pillars should systematise 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.

Requirements

• You are comfortable working with messy, behaviour-driven operations and translating observations into measurable signals.
• You have experience owning analytics for a network that depends on independent retailers and incentive-driven behaviour.
• You can investigate cost and behaviour problems by connecting in-app interactions with operational outcomes.
• You are able to sit with operators, watch handovers happen, and translate what you see into data questions and hypotheses.
• You can work with high operational cadence and move quickly between tactical investigations and strategic analysis.
• You are comfortable owning metrics end to end, from raw events to board-level dashboards.
• You have strong SQL skills to query large event datasets and join across operational and commercial tables.
• You can communicate clearly with both technical and non-technical stakeholders, explaining what the data says and what it does not say.

Nice to have

• Experience working with logistics, retail, or marketplace networks where incentives drive on-the-ground behaviour.
• Background in operations research, economics, or quantitative analysis applied to real-world systems.
• Familiarity with dbt, data modelling, and version-controlled analytics pipelines.
• Experience building dashboards in tools that integrate with modern data stacks.
• Background in e-commerce, delivery, or last-mile logistics.

Practical notes

-

Location: London

Hybrid.

-

Engagement: Full-time.

• The role reports into the Lead Data Analyst for Middle Mile, Pitstops & Sortation.
• You will sit in the Pitstop squad and work day-to-day with operations, sales, engineering, design, and research.
• The company operates a centralized data team of around 30 data engineers, analysts, and data scientists, with analysts embedded into squads across the business.

About the role

You will own the analytical layer that measures how the Pitstop network operates on a daily basis. You will translate messy, behaviour-driven operations into clear metrics that the squad can act on. You will investigate why handover speed varies, why some pitstops churn, and how in-app nudges change what happens on the counter. You will own the monitoring that lets the same team manage twelve times as many pitstops without adding people. You will sit at the intersection of operations, product, and data, turning real-world friction into measurable experiments. You will be the squad's source of truth for what is working, what is breaking, and where to intervene next. You will work closely with operators, engineers, and retailers to design systems that make the right behaviour the easy behaviour. You will maintain the dbt models and dashboards that keep every stakeholder aligned on the same numbers.

Key facts

What you'll do

• Own the Pitstop squad's five outcome metrics: Launch Velocity, Handover Speed, Handover Accuracy, Pitstop Retention, and Indirect Cost per Parcel, building the monitoring around them, investigating movement, and translating the numbers into next actions for the squad.
• Run the analytics behind pitstop performance and pricing, examining 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, measuring how much LiveOps load each self-serve flow removes, how much Middle Mile driver time each handover prompt unlocks, and what the CPP impact of retention work is on mature pitstops.
• Build launch readiness analytics, including 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, creating 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, quantifying what each ticket type costs, where the volume is concentrated, and which pillars should systematise 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.

Requirements

• You are comfortable working with messy, behaviour-driven operations and translating observations into measurable signals.
• You have experience owning analytics for a network that depends on independent retailers and incentive-driven behaviour.
• You can investigate cost and behaviour problems by connecting in-app interactions with operational outcomes.
• You are able to sit with operators, watch handovers happen, and translate what you see into data questions and hypotheses.
• You can work with high operational cadence and move quickly between tactical investigations and strategic analysis.
• You are comfortable owning metrics end to end, from raw events to board-level dashboards.
• You have strong SQL skills to query large event datasets and join across operational and commercial tables.
• You can communicate clearly with both technical and non-technical stakeholders, explaining what the data says and what it does not say.

Nice to have

• Experience working with logistics, retail, or marketplace networks where incentives drive on-the-ground behaviour.
• Background in operations research, economics, or quantitative analysis applied to real-world systems.
• Familiarity with dbt, data modelling, and version-controlled analytics pipelines.
• Experience building dashboards in tools that integrate with modern data stacks.
• Background in e-commerce, delivery, or last-mile logistics.

Practical notes

-

Location: London

Hybrid.

-

Engagement: Full-time.

• The role reports into the Lead Data Analyst for Middle Mile, Pitstops & Sortation.
• You will sit in the Pitstop squad and work day-to-day with operations, sales, engineering, design, and research.
• The company operates a centralized data team of around 30 data engineers, analysts, and data scientists, with analysts embedded into squads across the business.