Data Scientist

Pricing is one of the most direct levers ATG has for revenue growth, and the Pricing Data Science team has already proven that out through several pricing models now live in production. As the team scales across multiple growth areas, this hire is central to that expansion: working alongside Revenue Managers to build proofs of concept that make sure no revenue opportunity goes unexplored and helping size and prioritise the next models on the roadmap.

The role sits at the intersection of Revenue Management, CRM & Marketing, and ML Engineering, and needs someone who can operate credibly across all three.

In the near term, that means adding delivery capacity to two live work streams: the Sales-facing revenue quick-wins programme and the model backlog, with output from week one, not after a long ramp.

• Contribute directly to the live revenue quick wins workstream, translating commercial rules and constraints supplied by Sales into working model logic.
• Own discrete items from the model backlog end-to-end: specify, build, validate, and ship to production.
• Apply causal inference to pricing decisions at the same rigor the team already uses for VP measurement: difference-in-differences, Causal Impact/BSTS-style approaches, or comparable quasi-experimental design, with suppression and substitution effects accounted for rather than a naive before/after comparison
  
  Run two to three work streams concurrently with minimal supervision, and flag blockers and scope risk early rather than waiting to be asked.

• A proven track record of applied experience in pricing or revenue management analytics in a genuinely high-frequency, perishable-inventory, demand-variable domain: live events/ticketing, airline, hotel, sports, or transport RM. Ticketing/entertainment-sector experience is strongly preferred, not mandatory.
• Hands-on causal inference applied to a real pricing or promotional decision, not textbook familiarity: can describe, unprompted, how they handled confounding and selection bias on an actual dataset.
• Applied statistics/econometrics strong enough to defend a specific model choice (why OLS, why a GLM, why not a black-box model) rather than defaulting to whichever library was fastest to reach for.
• Demonstrated comfort switching between unrelated problems inside a single week without a long re-orientation each time.
• Direct pricing or revenue management experience in live entertainment or ticketing specifically.
• AWS ML stack experience (Sage Maker in particular), or a demonstrated fast translation from an equivalent platform.
• Experience with seat-map or other inventory-constrained demand modelling.
• Exposure to LLM/GenAI tooling inside a production analytics workflow.
• Python

• THRIVE doing what we love (with passion and dynamism)
• CONNECT through every act (with collaboration and kindness)
• DARE to do different (with curiosity and courage)
• PERFORM at our best (with customer focus and ownership)

• Inclusion:
  Committing to creating and upholding a positive, inclusive culture that nurtures potential and supports well-being.
• Sustainability:
  Playing your part in reducing our environmental impact and finding more sustainable ways of working.
• Next Generations:
  Encouraging the next generation in live entertainment by contributing to our outreach and training programmes, including mentoring students and trainees, and supporting our Creative Learning and Community Partnerships work.

You’ll help us uphold a positive culture around meeting our obligations, by having a positive attitude to health and safety, legal and insurance requirements and take care to understand our policies and procedures. We are all expected to participate actively in the life of the company, and opportunities will arise for you to collaborate with others across the business. Everyone at ATG Entertainment is expected to be flexible and adapt as the needs of the business change, taking on new or different responsibilities as the need arises.

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