Why this role stands out
Join Numan as a Senior Operations Analyst to drive meaningful impact within a high-growth health-tech leader, where your data-driven insights will directly shape the future of patient care. This role is perfect for a proactive problem-solver who thrives in a fast-paced environment and values the flexibility of a hybrid work culture. Apply today to accelerate your career and help build a platform that is revolutionizing healthcare on a global scale.
Quick overview
Job description
This is a high-impact data role supporting a complex and fast-paced operations function, reporting to the Director of Analytics & Data . You’ll be the analytics partner for Numan’s clinical operations, customer care, and health coaching teams, as well as our pharmacy and fulfilment centre.
These teams run on numbers. How long a patient waits for their prescription to be approved, or for a reply from a customer care agent. Whether there are enough coaches for the patients waiting. How many orders leave the pharmacy on time, and whether the stock is there to fill them. When a process changes, you’ll build the metrics that measure it and make sure the teams can trust them.
You’ll be the custodian of those metrics end to end, from the dbt models in BigQuery to the Looker dashboards the teams open every morning. Some are live queues the teams use to divert resources during the day; others feed the weekly business reviews and longer-term planning.
You will:
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Be the analytics partner for clinical operations, customer care, health coaching and the pharmacy and fulfilment centre, balancing each of their priorities and communicating timelines clearly. You’ll sit in their meetings and Slack channels, and be the first person they ask when questioning a number.
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Build and maintain the operations data models in dbt on BigQuery, and the Looker views, explores and dashboards on top of them.
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Be responsible for the surfacing of the 100+ metrics the operations teams report on (wait times and SLAs, per-hour productivity, audit scores, on-time dispatch, stock cover) and keep a written definition for each one.
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Help the teams build their demand forecasts and capacity plans, so the business knows how many people it needs and when.
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Explain why metrics move. Work out whether a change is real or can be explained by mix, reporting lag or a tracking problem, then find the cause and tell the team what to do about it.
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Help operations managers set targets and SLAs from a measured baseline, then track performance against them.
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Track the patient journey from checkout through prescription approval to first delivery, identifying where patients wait or drop out during the onboarding journey.
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Help the teams answer their own questions: walk new managers through their dashboards and explain what each metric means.
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Work with data engineering to model new data sources, and fix data quality problems when they show up.
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Occasionally support the commercial and finance teams with ad hoc analysis.
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Treat patient data with care. You’ll work with special category health data, so you’ll report in aggregate and follow UK GDPR.
You'll need:
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2-5yrs years experience as an analyst or analytics engineer, ideally in operations, customer service, healthcare or e-commerce fulfilment.
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Expert SQL, and hands-on experience building data models in dbt (or similar) and in Looker/LookML (or another BI tool). You’re comfortable with git and able to refine your work before it is reviewed.
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A good feel for operational metrics: queues and backlogs, wait times and SLAs, utilisation, productivity and forecasting.
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The ability to plan and prioritise your own work across several teams with competing requests. An understanding of how your work contributes to wider business objectives.
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Strong communication and relationship-building skills. Confidence presenting complex analysis to senior leaders.
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The ability to turn a vague question into a clear answer, and explain it simply to managers who don’t work with data every day.
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An understanding of data protection, and willingness to learn how UK GDPR applies to special category health data.
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Desirable: a background in pharmacy, clinical or healthcare operations; workforce planning; experience with tools such as Intercom, rota or inventory systems, or Amplitude; using AI assistants for analysis and code.
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