Role Purpose

This role is the analytical backbone of Veho's ground operations. On-Time Delivery (OTD) is the anchor: the person owns OTD analytics end to end and turns operational data into decisions the field and central ops can act on the same day. The mandate runs wider than OTD, though. This is the go-to analyst for transportation and middle-mile projects and for supply chain analytical work across the network, wherever central ops needs a rigorous, data-first answer. As Veho scales across markets and 3PL partners, the daily standup and OTD cadence only works if someone produces clean, trusted numbers and can explain why a metric moved, not just that it moved. The same person needs the range to pick up a transportation or network question cold and drive it to a recommendation. The job is two-handed. It takes enough rigor in SQL and analysis to root-cause a defect trend across hubs and zips or model a transportation lane, and enough resourcefulness to build the tooling that automates the work, increasingly by using AI to move faster than a traditional analyst could.
What Success Looks Like

First 6 Months

• Daily Standup and OTD Cadence Run on Trusted Numbers: The daily standup and weekly OTD reviews run on reporting this person owns: consistent definitions, reliable refreshes, no debate about whose number is right. Central ops and field leaders start the day aligned on what happened.
• Root-Cause, Not Just Reporting: When OTD moves in a market, hub, or for a client (Stord, Adidas, Ulta), this person can explain the drivers within hours using defect breakdowns, chronically underperforming zips, and hub-peer benchmarks. They don't hand over a dashboard and leave interpretation to someone else.
• Delivering Beyond OTD: Has taken at least one transportation or supply chain analytical project from question to recommendation, which proves the role's range extends past OTD reporting into network, labor, and cost problems.
• AI-Assisted Tooling Shipped: At least one useful piece of self-serve tooling or automated reporting is live, built hands-on with AI-assisted development, that removes recurring manual pulls and gives field leaders answers without routing through central. [TBD: target # of manual reports automated]
• Ad Hoc Analytics Turned Around Fast: Central ops and market leaders get high-quality ad hoc analysis on a tight turnaround, and the recurring questions become standing reports instead of getting re-run every week.
• Data the Field Actually Uses: Dashboards and reporting are adopted in the field, referenced in reviews and decisions rather than ignored. [TBD: self-serve adoption target]

12 Months

• OTD Analytics Is Self-Serve by Default: The routine OTD questions get answered by tooling this person built, which frees them to work the harder, non-obvious analyses. The function scales with the network without a matching rise in manual work.
• The Trusted Analytical Voice: This person is the go-to for OTD and for the transportation and supply chain questions central ops cares about. Leadership trusts their read of the data, and their analysis shapes where the network spends attention.
• A Reusable Analytics Toolkit: A library of queries, models, and AI-assisted tools makes each new market, client, or investigation faster to stand up than the last.

Key Responsibilities

OTD Analytics and Reporting Cadence

• Own the data and reporting behind the daily standup, OTD calls, and weekly and monthly OTD reviews: clean, reliable, consistently defined
• Produce the OTD read leadership and the field run on, covering defect rates, DPMP, and late-delivery drivers by market, hub, zip, and client
• Maintain trusted metric definitions so the cadence never stalls on whose number is right

Key metrics: OTD by market, DPMP, defect breakdown accuracy, on-time delivery of the reporting itself

Root-Cause and Ad Hoc Analysis

• Root-cause OTD movements. Separate what is actually driving a gap from what is merely correlated, across hub, zip, client, defect type, and hub-peer benchmarks
• Turn around ad hoc analytical requests from central ops and market leaders quickly and with rigor
• Convert recurring ad hoc questions into standing reports so they don't get re-run by hand

Key metrics: time-to-insight, share of recurring questions productized

Operational and Supply Chain Projects

• Own the roll-vs-run analysis (built by the current lead) and build a durable way to keep it current instead of rebuilding it by hand each time
• Labor and hours analysis: right-size staffing against volume and surface where hours are out of line with the work.
• Package loss and stow quality deep dives, turning each into analysis central ops can act on
• Pick up ad hoc network projects when capacity demands it

Key metrics: projects delivered, decision impact, quality of analysis

Tooling and Automation (AI-Assisted)

• Build self-serve dashboards and reporting tools hands-on, writing SQL and using AI-assisted development to ship faster than a traditional analyst workflow allows
• Automate repetitive operational reporting and monitoring to free up their own time and field leaders' bandwidth
• Manage all GO reporting tools and streamline all self build tooling
• Partner with the Bogota-based analytics-engineering function on anything that needs to be productionized or scaled beyond what one analyst can maintain

Key metrics: # of manual reports automated, self-serve adoption, tooling reliability
Ideal Candidate Archetype

Skillset

• SQL Fluency: Writes SQL comfortably and independently. Can go from a vague operational question to a clean, correct query without hand-holding. This is non-negotiable. The role lives in the data.
• AI-Assisted Building: Uses AI tools to build dashboards, scripts, and lightweight tooling faster than a traditional analyst. Not just a consumer of AI, but someone who has shipped working things with it. This is how the role keeps up with a scaling network.
• Analytical Rigor: Operates from data first. Can identify what is actually driving a performance gap versus what is merely correlated, and turn a messy operational dataset into a clear, defensible recommendation.
• Range Across Supply Chain: Comfortable working beyond OTD. Can pick up a transportation, labor, package-loss, or stow-quality question cold, scope it, and drive it to an answer. Curious and quick to learn a new part of the operation.
• BI and Spreadsheet Depth: Strong in BI tools and advanced Excel or Sheets. Builds reporting that field leaders trust and use.
• Operational Translation: Turns numbers into a story an ops person can act on. Knows the difference between a dashboard and an answer, and delivers the answer.
• Communication Under Time Pressure: Can stand up in a daily standup and explain what the data says clearly, on the spot, without a week of prep.

Leadership Traits

• Ownership: Treats the analytics as theirs. Chases down the data-quality issue and doesn't wait to be asked for the follow-up cut.
• Player Who Builds: At Veho's stage this person does the work: writes the query, builds the tool, runs the analysis. Comfortable being the whole function, not directing one.
• Moves with Velocity: Ships a good-enough V1, gets feedback, and iterates. Doesn't spend two weeks perfecting a dashboard nobody has seen yet.
• Direct Communicator: Says what the data shows, including when it is inconvenient or when a requested cut won't answer the real question.
• Systems Thinker: When the same manual pull comes up three weeks running, builds the tool instead of re-running it.
• Comfortable with Ambiguity: The analytics function is still being built. This person can define what good reporting looks like and build it, rather than waiting for a spec.

Experience

Must Have:

• 3+ years in analytics, BI, data analysis, or strategy and operations, with meaningful hands-on time in the data rather than presenting other people's work
• Strong, demonstrable SQL skills. Has independently written the queries behind real reporting or analysis
• Has built dashboards or reporting tooling hands-on, and has used AI tools to speed up that building
• Background in a physical, high-volume operations environment (logistics, fulfillment, last-mile, e-commerce ops), or clear evidence they pick up operational context fast
• Track record turning ambiguous operational questions into clear analysis on a tight turnaround
• Range across more than one analytical area. Has done transportation, network, labor, or cost analysis on top of performance reporting, not a single-metric specialist

Good to Have:

• Experience at a tech-enabled operator and time at a high-growth startup
• Familiarity with Databricks or warehouse-scale SQL
• Exposure to on-time delivery, defect, or delivery-quality metrics
• Experience supporting an operating cadence (standups, ops reviews) with live reporting