Assessment Delivery Optimisation, Scarlet

• Experience building or operating production forecasting, optimisation or scheduling systems
• Experience using data modelling and analytics to drive operational decisions, with strong hands-on skills
• Experience using AI to improve operational workflows, including evaluating when their outputs are reliable enough to use
• Experience leading cross-functional decisions involving teams with competing priorities
• Experience explaining complex operational decisions clearly

Desirable

• As Scarlet's first Assessment Delivery Optimisation hire, you will own how Scarlet plans, prioritises and deploys assessment resources across our whole customer portfolio
• You will build the operating model for a fast-growing portfolio: in twelve months’ time, we expect to serve roughly four times today's customer base — assessing all types of devices, across a range of regulatory frameworks and standards
• You will solve a complex global scheduling problem
• Our assessment experts are distributed around the world, many work part-time or as contractors, and some customer assessments must happen in person
• You will build systems that match each assessment with the right expertise, location and timing
• You will combine operational judgement, data modelling and AI to build planning and deployment systems that keep every assessment moving, from demand forecasting to real-time prioritisation across the portfolio
• Your work will determine how quickly safe medical devices reach the patients who need them
• Own portfolio-level capacity planning: forecast how much assessment resource, and of what type, we will need at a given time to meet demand, to ensure hiring and onboarding plans are aligned with capacity needs
• Design and optimise how assessment experts are allocated to work, including who performs each activity and when it can begin
• Own and improve the scheduling and prioritisation tools used to track evaluator availability, customer availability and qualification status across certification regimes
• Partner with product, engineering and machine learning teams to build tools that support automation of large-scale assessment operations

• Intro call with Emily — 30 mins
• Team interviews — 2 x 45 mins
• Problem-solving interview — 60 mins
• Culture and values interviews with James and Jamie — 2 × 30 mins