We’re on a mission to create a diverse group of future leaders. We do that through professional apprenticeships because we believe learning on-the-job creates a more equitable and successful path to careers. We find, train and support talented individuals, wherever they are in their career journey, and equip them with the in-demand tech, software engineering, and data skills to transform their careers and deliver a better route to growth for their employers.

We’ve had some big achievements. We hit 10,000 apprentices in our community - and counting. We launched one of the largest data apprenticeship programs in the UK with Jaguar Land Rover, and we’ve partnered with companies like Mars, Verizon and CitiBank. Not to forget becoming a mission-driven EdTech unicorn after our $220m Series D.

But we aren’t stopping here. Join Multiverse and build the future of learning at work.

The Director of Marketplace Optimisation will use data analytics, forecasting, and sound strategy design to craft our efforts to improve Multiverse’s business while strengthening our platform’s sustainability. The Multiverse learning platform serves as an emerging marketplace — with increasingly complex product and learning tools (e.g., multiple program domains, customer service tiers, learning channels, and infinite pathways). The Director of Optimisation will analyse and forecast these marketplace dynamics to enable data driven decision making, proper planning, and will own creation of operational strategies (playbooks) to enable real-time trade-offs in quality and efficiency to create marketplace equilibrium.

In short, this person will balance Multiverse’s multi-sided marketplace across our ecosystem of customers (large companies), apprentices (learners), and coaches (instructional resources).

This is achieved by combining economic, marketplace, and financial acumen with forecasts, learning requirements, and operational data to understand and predict demand for specific Multiverse services, and to tie findings to decisions teams can make to ensure proper real-time resourcing.

The candidate will report to the VP of Global Operations, and develop considerable working relationships across senior Multiverse leadership in central operations, finance, data, product, and learning teams. This is an initial optimisation hire, and the successful candidate will have an opportunity to build and grow our internal marketplace and strategy function.

Key responsibilities:

• Forecast and analyze demand for instructional support across multiple domains, service tiers, and learner types (globally and regionally)

• Understand our learning and product features and how they interact with the wider ecosystem; you will provide guidance on best practices to operations teams and make actionable recommendations to balance the tradeoffs in our marketplace

• Develop and own 4-5 primary cross-org strategies (e.g., channel substitution) to ensure Multiverse maintains flexibility to hit quality guardrails, maximize efficiency, while adapting to any constrained instructional capacity

• Work with operating teams to plan and design experiments for demand, supply and market clearance levers (e.g. learner persona development, product feature, etc.).

• Communicate models and strategies across internal stakeholders

• Use outputs to recommend automatons of existing processes to maximize business and customer objectives (help shape direction of our tech roadmap)

• Conduct quantitative and qualitative research to assess user behavior to predict requirements and improve service offering (efficiency and quality)

• Excited to build a new team, a leader that is willing to get their hands in the details and conduct analysis, but can zoom out and provide high level strategy

Requirements

• Experienced in demand forecasting, marketplace strategy, and able to translate analysis into actionable recommendations (e.g., set the strategy for creating marketplace equilibrium)

• At least 7 years of relevant work experience (Analytics, Business Intelligence, Management Consulting, Banking, or strategy roles in a tech company)

• Prior experience in handling large, complex, high velocity data; familiar with common statistical, analytical and ML techniques; willing to continue to learn/apply new techniques as required.

• Ability to distill insights & articulate an actionable point of view to non-technical audiences; Comfortable presenting to senior stakeholders; Good command of storytelling and presentation techniques (e.g., data visualisation).

• Has led multidisciplinary problem solving exercises that results in clear business (measurable financial) impact

• Ability to handle multiple priorities and solve ambiguous problems that may evolve in scope or complexity

• Experience with SQL, tableau, alteryx, and other self-serve data analysis and visualization tools

Benefits

• Time off - 27 days holiday, plus 7 additional days off: 1 life event day, 2 volunteer days and 4 company-wide wellbeing days

• Health & Wellness- private medical Insurance with Bupa, a medical cashback scheme, life insurance, gym membership & wellness resources through Gympass and access to Spill - all in one mental health support

• Hybrid & remote work offering - with weekly or monthly visits to the London office and the opportunity to work abroad 45 days a year

• Team fun - weekly socials, company wide events and office snacks!

Our commitment to Diversity, Equity and Inclusion

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.

Safeguarding

All posts in Multiverse involve some degree of responsibility for safeguarding. Successful applicants are required to complete a Disclosure Form from the Disclosure and Barring Service ("DBS") for the position. Failure to declare any convictions (that are not subject to DBS filtering) may disqualify a candidate for appointment or result in summary dismissal if the discrepancy comes to light subsequently.