Key Skills

Job Description

About Choice Logistics Choice Logistics is a global 4PL provider of mission-critical service parts logistics for the healthcare, telecom and data center industries. When a hospital imaging system, a mobile network node or a hyperscale data center goes down, our clients rely on us to get the right part to the right place within hours, anywhere in the world. We orchestrate a network of forward stocking locations, carriers and partners across 100+ countries, and we measure ourselves in minutes, not days. The role: This is a new position, and the person who takes it will define it. Our EMEA - APAC Operations teams run thousands of time-critical orders a day, and today we measure that work through a mix of exports, spreadsheets and individual reports. We are building a proper performance management framework for Operations — the KPIs, the definitions behind them, the cadence they are reviewed on, and the tooling that makes them visible — and you will own it, from design through to daily use. Half of this job is technical: building the dashboards and reports in Python and Tableau that operations leaders, team leads and analysts actually open every morning. The other half is not technical at all: sitting with those teams, understanding how the work really flows, hearing the problem behind the request they made, and turning that into something measurable. You will prototype fast, put rough versions in front of people early, take the feedback, and iterate until it sticks. Then you'll make sure it gets adopted. This is not a reporting-desk role and it is not a pure data engineering role. If you want to spend your days executing a backlog of ticket requests, or you prefer to work from a finished spec, this will not be a good fit. If you like being handed an ambiguous operational question and owning the answer end to end, read on. What you will do: Build the performance management framework: Define, with Operations leadership, the KPI hierarchy for EMEA - APAC Operations execution: order cycle time, SLA attainment, exception and escalation rates, inventory accuracy, cost-to-serve, productivity and quality measures. Own the metric definitions and the data logic behind them so that one number means one thing across teams, sites and clients. Design the review cadence (daily, weekly, monthly) and the artifacts each level of the organization uses. Lead the implementation and drive adoption; a framework nobody uses is a failure regardless of how well it was designed. Build the measurement tools: Design and develop dashboards and automated reports in Tableau, with data preparation, transformation and automation in Python. Take each product through the full cycle: ideation with the business, prototype, business sign-off, deployment, and post-launch iteration. Use AI tooling (code assistants, LLM-based analysis, automation) deliberately to shorten development cycles and raise the quality of what you ship. Maintain what you build. Document it well enough that it survives you. Work with the business Run requirements sessions with Operations, Client Services, Network/Inventory and Finance teams across EMEA - APAC; understand what they ask for and what they actually need. Translate operational pain into measurement: propose the metric, show why it matters, and demonstrate what will change once it's visible. Manage stakeholders at team-lead through director level, including the difficult conversations when a metric shows a team in an unfavorable light. Feed the broader Operational Excellence and continuous improvement agenda with insights from the data — surface the root causes, not just the symptoms. What we are looking for Must have — we will screen on these 5+ years in a business analyst, operations analyst, performance/BI analyst or similar role, in logistics, supply chain, transportation, distribution or field-service operations. You understand what an SLA breach, a stock-out, a cut-off time or a reverse-logistics flow means operationally, not just in a data model. Tableau at a level where you have designed and shipped dashboards that a business ran on, not just consumed or lightly edited existing ones. Python for data work: pandas or equivalent, working with databases/APIs, automating data pipelines and reporting. You should be comfortable being the person who wrote the code, not the person who requested it. Demonstrable ownership of at least one analytics or measurement product from ideation through business adoption. Strong stakeholder management: evidence of working directly with operational teams and leadership, aligning conflicting views, and securing buy-in for something new. Experience working in Agile / iterative delivery: short cycles, prototypes over specs, frequent feedback. Fluent English; comfortable working across multiple EMEA - APAC countries and time zones. Strong plus Practical, day-to-day use of AI tools to accelerate development (e.g., AI-assisted coding, LLM-driven analysis or documentation, agentic automation), with clear examples of where it made you faster or better. SQL and familiarity with WMS / TMS / OMS data structures. Exposure to Lean, Six Sigma or a structured continuous-improvement methodology. Experience in a 3PL/4PL, service-parts or time-critical logistics environment. Additional European languages. This role is probably not for you if Your BI experience is primarily in retail, marketing or finance reporting with no operations exposure. You have used Tableau or Python mainly in a coursework, certification or personal-project context. You prefer clearly specified requirements and a stable backlog to ambiguity and iteration.

Core Responsibilities

Design and own an operational performance management framework for EMEA–APAC, including KPI definitions, review cadence, and adoption across teams. Build and maintain Tableau dashboards and Python-based reporting tools, partnering with stakeholders to turn operational needs into measurable insights and continuous improvements.

Requirements

Requires 5+ years of relevant business, operations, performance, or BI analysis experience in logistics, supply chain, transportation, distribution, or field-service operations, plus hands-on Tableau dashboard development and Python data automation. Candidates should demonstrate end-to-end ownership of an analytics product, strong stakeholder management, iterative delivery experience, and fluent English.