At a Glance
- Tasks: Dive into pricing optimisation strategies and develop models using Python.
- Company: Join a global leader in pricing and revenue intelligence, recently expanded through a startup acquisition.
- Benefits: Enjoy a competitive salary and the chance to work with cutting-edge technology.
- Other info: Work independently while contributing to a culture of intellectual curiosity.
- Why this job: Tackle complex, research-driven problems that have a real-world impact in travel and hospitality.
- Qualifications: PhD or Master's in a quantitative field; strong Python and statistical modelling skills required.
The predicted salary is between 60000 - 70000 £ per year.
Senior Pricing Optimisation Data Scientist
Location: UK-based
Salary: £60,000 – £70,000
The Opportunity
Join a global leader in pricing and revenue intelligence, recently expanded through the acquisition of a high-growth startup. As part of a specialised team of highly academic Data Scientists, you’ll contribute to cutting-edge pricing algorithms that help reshape decision-making in travel and hospitality industries.
This is a deeply analytical role that values theoretical understanding and scientific thinking over production engineering. If you enjoy complex, research-driven problems with real-world impact – this is for you.
What You\'ll Do
- Conduct deep research into pricing optimisation strategies for hotel revenue
- Develop models in Python using Pandas, statistical tooling, and custom algorithms
- Translate real-world pricing problems into mathematical and statistical frameworks
- Work independently and contribute to a culture of intellectual rigor and curiosity
Ideal Profile
- PhD in Mathematics, Statistics, Physics, or a related quantitative field (Master’s with significant pricing optimisation experience considered)
- Strong foundation in statistical modelling, optimisation, and machine learning fundamentals
- Fluent in Python and data science tools (e.g., Pandas, NumPy)
- Prior experience in revenue management or pricing is a plus, but not required
Interview Process
- Intro chat
- Take-home exercise and presentation
- Sign off chat
Senior Pricing Optimisation Data Scientist in Brighton employer: Harnham
As a global leader in pricing and revenue intelligence, this company offers an exceptional work environment for Senior Pricing Optimisation Data Scientists, fostering a culture of intellectual curiosity and rigorous analysis. Employees benefit from competitive salaries, opportunities for professional growth, and the chance to work on impactful projects that shape the future of the travel and hospitality industries. With a focus on collaboration and innovation, this UK-based role provides a unique opportunity to engage with cutting-edge research while being part of a dynamic team.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Pricing Optimisation Data Scientist in Brighton
✨Tip Number 1
Familiarise yourself with the latest trends in pricing optimisation and revenue management. Being able to discuss current methodologies and innovations during your interview will demonstrate your passion and knowledge in the field.
✨Tip Number 2
Brush up on your Python skills, especially with libraries like Pandas and NumPy. Consider working on personal projects or contributing to open-source projects that involve data analysis and statistical modelling to showcase your practical experience.
✨Tip Number 3
Prepare to discuss complex problems you've solved in the past, particularly those involving mathematical frameworks. This will help you illustrate your analytical thinking and problem-solving abilities, which are crucial for this role.
✨Tip Number 4
Network with professionals in the pricing and data science fields. Engaging with industry experts can provide insights into the role and may even lead to referrals, increasing your chances of landing an interview with us.
We think you need these skills to ace Senior Pricing Optimisation Data Scientist in Brighton
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights relevant experience in data science, particularly in pricing optimisation and statistical modelling. Use specific examples that demonstrate your skills in Python and any related tools.
Craft a Compelling Cover Letter:Write a cover letter that showcases your passion for data science and your understanding of the travel and hospitality industries. Mention how your academic background aligns with the role and express your enthusiasm for contributing to innovative pricing algorithms.
Highlight Relevant Projects:If you've worked on projects involving pricing strategies or data analysis, be sure to include these in your application. Describe your role, the tools you used, and the impact of your work to demonstrate your capability.
Prepare for the Interview Process:Familiarise yourself with common interview questions for data scientists, especially those related to statistical modelling and optimisation. Be ready to discuss your take-home exercise and present your findings clearly and confidently.
How to prepare for a job interview at Harnham
✨Showcase Your Analytical Skills
Prepare to discuss your experience with statistical modelling and optimisation. Be ready to explain how you've applied these skills in previous roles or projects, especially if they relate to pricing strategies.
✨Demonstrate Your Python Proficiency
Since the role requires fluency in Python and data science tools, brush up on your coding skills. You might be asked to solve a problem using Pandas or NumPy during the interview, so practice coding exercises beforehand.
✨Prepare for the Take-Home Exercise
The take-home exercise is a crucial part of the interview process. Make sure you understand the requirements clearly and allocate enough time to complete it thoroughly. Present your findings in a clear and structured manner.
✨Engage in Intellectual Curiosity
This role values a culture of intellectual rigor. Be prepared to discuss recent trends in pricing optimisation and how they could impact the travel and hospitality industries. Show your passion for research-driven problems and your eagerness to learn.
