Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and deploy high-frequency demand forecasting models for pricing decisions.
- Company: Join a Series D tech scale-up revolutionising travel and hospitality with advanced machine learning.
- Benefits: Enjoy remote work, private healthcare, mental health support, nursery benefits, and generous PTO.
- Why this job: Be part of a world-class data science team driving global commercial strategies with cutting-edge technology.
- Qualifications: Strong background in statistics, machine learning, and proficiency in production-level Python code required.
- Other info: Work in a modern MLOps setup and contribute to company-wide data science libraries.
The predicted salary is between 42000 - 84000 £ per year.
A Series D tech scale-up is reshaping the travel and hospitality industries through advanced machine learning and forecasting. Purpose-built for this space, their platform leverages deep learning to drive revenue optimisation, automation, and real-time analytics. With a growing client base of major global travel brands, they’re hiring exceptional talent to push the boundaries of what’s possible in commercial strategy.
As a Senior Data Scientist within the Forecasting Algorithms team, you will design and deploy high-frequency demand forecasting models that directly support pricing decisions. You’ll own the full development lifecycle—from modelling to deployment—while collaborating closely with science, product, and engineering stakeholders. This is a hands-on role suited to someone who thrives on building, testing, and deploying complex statistical models in a production environment. You’ll work in a modern MLOps setup, contributing to libraries and frameworks used across the company’s data science organisation.
Key Responsibilities:- Design and deploy time series forecasting models with a strong focus on accuracy and scalability
- Improve existing model performance and drive innovation through new methodologies
- Develop internal ML and forecasting libraries using Python
- Translate product goals into technical solutions in collaboration with leadership
- Implement validation frameworks, unit tests, and monitoring pipelines
- Stay current with advances in machine learning and apply them where appropriate
- Python (Pandas, Polars, SciPy, Scikit-learn, NumPy)
- Dagster, Argo, GCP
- Kibana, Elastic
- DevOps-first approach for model deployment
- Strong background in statistics, machine learning, and time series forecasting
- Experience with modern ML models (e.g. transformers, CNNs, attention mechanisms)
- Proficiency in writing production-level Python code
- Familiarity with CI/CD practices, testing, and model validation
- Confident working across teams and taking ownership of delivery
- Strong communication and problem-solving skills
- Experience in demand forecasting or operations research
- Familiarity with Bayesian methods, Monte Carlo simulations, or reinforcement learning
- Exposure to high-scale SaaS or B2C products
Why Apply? Build forecasting systems powering global commercial strategies. Collaborate with a world-class data science team. Up to £70,000 + equity in a high-growth AI company. Excellent benefits: private healthcare, mental health support, nursery benefit (UK), and generous PTO.
How to Apply: To apply, please send your CV to Daniel Abbasi via the Apply link on this page.
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist
✨Tip Number 1
Familiarise yourself with the specific technologies mentioned in the job description, such as Python libraries like Pandas and Scikit-learn. Being able to discuss your experience with these tools during an interview will demonstrate your technical fit for the role.
✨Tip Number 2
Showcase your understanding of time series forecasting by preparing examples of past projects where you've successfully implemented similar models. This will help you stand out as a candidate who can directly contribute to the team's goals.
✨Tip Number 3
Network with current or former employees of the company on platforms like LinkedIn. Engaging with them can provide insights into the company culture and expectations, which you can leverage during your interview.
✨Tip Number 4
Stay updated on the latest advancements in machine learning and be prepared to discuss how you can apply these innovations to the role. This shows your commitment to continuous learning and your ability to drive innovation within the team.
We think you need these skills to ace Senior Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in statistics, machine learning, and time series forecasting. Emphasise any projects where you've designed or deployed forecasting models, as this aligns closely with the role.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data science and how your skills can contribute to the company's mission. Mention specific technologies from their tech stack that you are proficient in, such as Python and modern ML models.
Showcase Your Problem-Solving Skills: Provide examples in your application of how you've tackled complex problems in previous roles. Highlight your experience with model validation and CI/CD practices, as these are essential for the position.
Highlight Collaboration Experience: Since the role involves working across teams, mention any past experiences where you've collaborated with product and engineering stakeholders. This will demonstrate your ability to communicate effectively and take ownership of delivery.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and the specific libraries mentioned in the job description, such as Pandas and Scikit-learn. Highlight any projects where you've designed and deployed forecasting models, as this will demonstrate your hands-on experience.
✨Understand the Company’s Focus
Research the company’s approach to machine learning and how they apply it within the travel and hospitality industries. Being able to articulate how your skills can contribute to their goals will set you apart from other candidates.
✨Prepare for Problem-Solving Questions
Expect to face technical questions that assess your problem-solving abilities. Practice explaining your thought process when tackling complex statistical models or improving existing ones, as this will showcase your analytical skills.
✨Emphasise Collaboration and Communication
Since the role involves working closely with various teams, be ready to discuss your experience in cross-functional collaboration. Share examples of how you've effectively communicated technical concepts to non-technical stakeholders.
