Data Scientist - Price Optimisation

Location: Remote (UK-based, London preferred)

Salary: £60,000-£70,000 + 5-8% bonus + Equity

A global pricing and revenue optimisation leader originally focused on airline pricing, now expanding into the hotel and hospitality sector. Following the acquisition of Pace Revenue, the team in the UK forms a key part of their hotel pricing division, operating under the same Flyr brand.

This is a deeply analytical and research-driven role within the Pricing Optimisation team. You'll be focusing on advanced mathematical modelling and pricing logic development to enhance the company's pricing engine. Unlike traditional ML-focused roles, this will go deeper into statistical theory and pricing dynamics to influence global product strategy.

- Research and develop advanced pricing models for hotel revenue optimisation.

- Work closely with other data scientists and engineers to deploy new logic.

- Collaborate on experimentation, testing and performance evaluation.

- Present findings to technical and non-technical stakeholders.

- Contribute to long-term pricing strategy alongside product and business teams.

Essential:

- PhD in a mathematics, statistics or quantitative field (or Master's with strong pricing experience).

- Excellent Python and Pandas skills.

- Strong understanding of machine learning principles (excluding deep learning).

- Ability to work independently on complex mathematical problems.

- Research-led mindset with a passion for optimisation.

Desirable:

- Experience with pricing in hospitality or travel sectors.

- Familiarity with academic or research environments.

You'll join the Pricing Optimisation team, working alongside 3 Senior Data Scientists under the management of James Butler. The wider DS function includes a Forecasting team and engineering support, with additional collaboration across global locations.

- 5-8% performance bonus (depending on level)

- Equity

- Private healthcare

- 25 days holiday

- Nursery benefit (tax-free)

- Remote-first working policy (UK only)

1st Stage: Intro chat with DS Manager

2nd Stage: Live technical screen share coding task (1 hour)

3rd Stage: Take-home task (up to 3 hours)

4th Stage: Presentation (30 mins)

5th Stage: Deep dive on ML and culture fit

Final Stage: VP sign-off conversation

Send your CV to Mohammed Buhariwala at Harnham or reach out directly for more information about the opportunity.