Job Template (UK)
UK Visa Sponsorship Analytics
Analytics are greyed out due to low classification confidence (48.0%).
Occupation TypeTool makers, tool fitters and markers-out
Occupation Code Skill LevelMedium Skilled
Sponsorship EligibilityIneligible for Sponsorship
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Description
Multiverse is the upskilling platform for AI and Tech adoption.
We have partnered with 1,500+ companies to deliver a new kind of learning that's transforming today’s workforce.
Our upskilling apprenticeships are designed for people of any age and career stage to build critical AI, data, and tech skills. Our learners have driven $2bn+ ROI for their employers, using the skills they’ve learned to improve productivity and measurable performance.
In June 2022, we announced a $220 million Series D funding round co-led by StepStone Group, Lightspeed Venture Partners and General Catalyst. With a post-money valuation of $1.7bn, the round makes us the UK’s first EdTech unicorn.
But we aren’t stopping there. With a strong operational footprint and 800+ employees, we have ambitious plans to continue scaling. We’re building a world where tech skills unlock people’s potential and output.
Join Multiverse and power our mission to equip the workforce to win in the AI era.
Why This Role Exists
Multiverse is evolving from a services-led organisation into an AI-first, platform-led workforce transformation company. Our 200+ coaches are the mechanism through which learning translates into measurable business outcomes. To scale to $1bn+ in bookings, the system that deploys those coaches against variable demand must be as disciplined as the coaching itself. Today, workforce management, capacity planning, and allocations operate through manual processes, fragmented data, and institutional knowledge. The function works, but it does not scale. This role exists to build the supply engine that fuels delivery. Not delivery itself.
Role Overview
You will translate demand forecasts into coach deployment, build and operate the matching engine that pairs coaches with learners, and lead the analytical intelligence layer across the full operations machine. You are not building a reporting team. You are building an operational engine: automated and rule-based for routine allocations, with a designed escalation path for complex matches where delivery leadership makes the final call. The analytics function you lead will serve as the shared data backbone across coach platform, process automation, support, fulfilment, and the delivery organisation.
Primary Responsibilities
We have partnered with 1,500+ companies to deliver a new kind of learning that's transforming today’s workforce.
Our upskilling apprenticeships are designed for people of any age and career stage to build critical AI, data, and tech skills. Our learners have driven $2bn+ ROI for their employers, using the skills they’ve learned to improve productivity and measurable performance.
In June 2022, we announced a $220 million Series D funding round co-led by StepStone Group, Lightspeed Venture Partners and General Catalyst. With a post-money valuation of $1.7bn, the round makes us the UK’s first EdTech unicorn.
But we aren’t stopping there. With a strong operational footprint and 800+ employees, we have ambitious plans to continue scaling. We’re building a world where tech skills unlock people’s potential and output.
Join Multiverse and power our mission to equip the workforce to win in the AI era.
Why This Role Exists
Multiverse is evolving from a services-led organisation into an AI-first, platform-led workforce transformation company. Our 200+ coaches are the mechanism through which learning translates into measurable business outcomes. To scale to $1bn+ in bookings, the system that deploys those coaches against variable demand must be as disciplined as the coaching itself. Today, workforce management, capacity planning, and allocations operate through manual processes, fragmented data, and institutional knowledge. The function works, but it does not scale. This role exists to build the supply engine that fuels delivery. Not delivery itself.
Role Overview
You will translate demand forecasts into coach deployment, build and operate the matching engine that pairs coaches with learners, and lead the analytical intelligence layer across the full operations machine. You are not building a reporting team. You are building an operational engine: automated and rule-based for routine allocations, with a designed escalation path for complex matches where delivery leadership makes the final call. The analytics function you lead will serve as the shared data backbone across coach platform, process automation, support, fulfilment, and the delivery organisation.
Primary Responsibilities
Build and Run the Allocations Engine (~35%)
- Define, build, and operate the system that translates demand into coach deployment. Own time-to-fill, allocation process cost, and bench and contractor flex decisions that keep the supply model solvent
- Design the matching engine: routine, low-risk allocations run automatically; delivery owns the final decision where coach capability, learner context, and programme nuance require human judgment
- Iterate the engine as the delivery model evolves toward Operating Model 2.0, including non-standard capacity modelling for new programmes, customisations, and DPT scaling
- Coordinate dedicated analytical resources (one data Senior Manager, three analysts) as the shared data backbone across the full ops machine
- Standing outputs: utilisation, bench duration, forward demand coverage, forecast accuracy, operating model performance. Surface the right data to the right consumers in the right cadence
- Ingest demand plans from finance and RevOps, translate into supply plans, produce resource-required projections that feed hiring and budget decisions
- Serve as the named counterpart to delivery leadership on match quality trade-offs; own the stakeholder feedback loop on allocation quality
- Build the tools and RACIs to decentralise budget ownership across individual VPs and Senior Directors
- Ad hoc modelling: operating model transition scenarios, restructure modelling, cost-to-serve deep dives, DPT operationalisation business cases
- Steer the systems and tooling investment that moves this function from manual to automated. Ring-fenced build capacity with time-bound exit criteria
First Six Months
- Produce a full scoping document for the future-state WFM system: fully automated, flexible, supporting the future delivery model, and fully absorbing allocations with no (or streamlined) inputs from operations SPCs and leaders
- Build the tools, capability, and RACIs to hand over centralised budgeting into its component parts
- Take full ownership of departmental delivery models (transitioning from the current owner) to standardise execution
- Serve as de facto PM for DPT operationalisation, which directly overlaps with service tiers and downstream allocations impact
- Establish the analytical operating rhythm: standing reports, consumption cadence, and the interface with finance, RevOps, and delivery
- 10+ years in workforce planning, resource management, or capacity operations, with direct experience deploying a skilled, non-interchangeable workforce against variable demand. Professional services, scaled BPO, workforce marketplace platforms, or similar environments where match quality matters as much as fill rate
- You have systematised at least one manual operational function. You know the difference between automating a bad process and redesigning the work
- You commission and consume analysis confidently. You ask the right questions of a data team, challenge the outputs, and translate findings into operational decisions. You do not need to build the models
- You have been the named counterpart between a planning function and an execution function, and you understand that the failure mode is the handover design, not which side owns the work
- Clear point of view on practical AI adoption in operations. You understand that AI is the engine, not an add-on
- Experience building a workforce planning or resource operations function from manual or early-stage to systematised and automated
One Allocations Lead who owns the matching engine as a product. One Non-Standard Capacity Lead for customisations and new programmes. One Data Senior Manager leading three analysts. TBD build resource for systems and tooling implementation, ring-fenced with a time-bound deliverable.
Metrics You Own
Forecast accuracy and bias, time-to-fill, bench duration, forward demand coverage, allocation process cost, utilisation rate (tracked as a guardrail against the operating model). Match quality is shared: Ops owns the engine and the data; delivery owns the final matching decision on complex allocations. Stakeholder satisfaction is a feedback loop: delivery surfaces issues, this function recalibrates.
Benefits
- Time off - 27 days holiday, plus 5 additional days off: 1 life event day, 2 volunteer days, 2 company-wide wellbeing days (M-Powered Weekend) and 8 bank holidays per year
- Health & Wellness- private medical Insurance with Bupa, a medical cashback scheme, life insurance, gym membership & wellness resources through Wellhub and access to Spill - all in one mental health support
- Hybrid work offering - for most roles we collaborate in the office three days per week with the exception of Coaches and Instructors who collaborate in the office once a month
- Work-from-anywhere scheme - you'll have the opportunity to work from anywhere, up to 10 days per year
- Space to connect: Beyond the desk, we make time for weekly catch-ups, seasonal celebrations, and have a kitchen that’s always stocked!
We’re an equal opportunities employer. And proud of it. Every applicant and employee is afforded the same opportunities regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. This will never change. Read our Equality, Diversity & Inclusion policy here.
Our Commitment to Safeguarding
Multiverse is committed to safeguarding and promoting the welfare of our learners. We expect all employees to share this commitment and adhere to our Safeguarding Policy, our Prevent Policy and all other Multiverse company policies. Successful applicants will be required to undertake at least a Basic check via the Disclosure Barring Service (DBS).
For roles that will involve a Regulated Activity, successful applicants must also undergo an Enhanced DBS check, including a Children’s Barred List check and a Prohibition Order check. Roles involving Regulated Activity may interact with vulnerable groups, therefore are exempt from the Rehabilitation of Offenders Act 1974 meaning applicants are required to declare any convictions, cautions, reprimands, and final warnings.
Providing false information is an offence and could result in the application being rejected or summary dismissal if the applicant has been selected, and possible referral to the police and the DBS.
Our Commitment to Safeguarding
Multiverse is committed to safeguarding and promoting the welfare of our learners. We expect all employees to share this commitment and adhere to our Safeguarding Policy, our Prevent Policy and all other Multiverse company policies. Successful applicants will be required to undertake at least a Basic check via the Disclosure Barring Service (DBS).
For roles that will involve a Regulated Activity, successful applicants must also undergo an Enhanced DBS check, including a Children’s Barred List check and a Prohibition Order check. Roles involving Regulated Activity may interact with vulnerable groups, therefore are exempt from the Rehabilitation of Offenders Act 1974 meaning applicants are required to declare any convictions, cautions, reprimands, and final warnings.
Providing false information is an offence and could result in the application being rejected or summary dismissal if the applicant has been selected, and possible referral to the police and the DBS.