Engineer the Quantum RevolutionYour expertise can help us shape the future of quantum computing at Oxford Ionics.

View Open Roles

Senior Data Scientist

Central Parking
Manchester
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist - Computer Vision

Senior Data Scientists

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

About CAVU:

For airports, for partners, for people. We are CAVU.


At CAVU our purpose is to find new and better ways to make airport travel seamless and enjoyable for everybody. From the smallest ideas to the biggest changes. Every day here is about creating better travel experiences.


From our revenue-accelerating single platform technology, Propel, through to our world-class hospitality venues including 1903 and Escape Lounges — our solutions make travel more seamless and enjoyable for passengers, and more profitable for our clients and partners.


We know that to bring your best ideas, you need the space to think, the right support, and the freedom to be your true, authentic self.


Whether you’re working from our offices, from home, in a lounge, or out on the road, we provide the environment to create, innovate, and transform airport travel.


If you’re looking for a career where you can make a real impact, bring new ideas to life, and push boundaries, then CAVU is the place for you.


Together, we can reach new heights. Together, we are CAVU.


What's the role:


TheSenior Data Scientistis a vital part of the centralised Data team at CAVU, acting as a consultant for the diverse business areas we serve. You’ll play a key role in shaping the future of CAVU’s data science capability, accelerating the use of advanced analytics, and embedding data-driven decision making across the organisation.


As our new Senior Data Scientist, you’ll work on exciting projects including productionising forecasting algorithms, developing classification models, exploring customer behaviours, and supporting personalisation strategies — with opportunities to work on NLP projects too.


You’ll also take ownership of projects, support our data science tooling (including Databricks and AWS), and collaborate closely with experts in Data Engineering, BI, Analytics, and Data Governance to solve problems and create scalable solutions that make a tangible difference.


What’s in it for you?


This is a brilliant opportunity to join CAVU’s Data team at a pivotal time in our digital and data transformation journey. You’ll work with cutting-edge tools and cloud technologies, contribute to innovative data science projects, and help shape how CAVU uses data science to power decision making and customer experiences.


You’ll have the freedom to bring your ideas to life, support and mentor others, and continuously develop your skills in a collaborative, hybrid working environment.


About you


Role Responsibilities:

Design, build, and maintain scalable machine learning pipelines using Python and PySpark.


Work within Databricks to develop, schedule, and monitor data workflows, utilising Databricks Asset Bundles.
Collaborate with data analysts, engineers, and other scientists to deliver clean, reliable, and well-documented datasets.
Develop and maintain CI/CD pipelines for testing, deployment, and delivery of data science solutions.
Support data modelling and transformation for analytics and reporting needs.
Contribute to continuous improvements in our data science practices, testing frameworks, and deployment processes.
Mentor and support more junior colleagues, fostering a culture of learning and knowledge sharing.
Scope out requirements and deliverables in an agile way, ensuring successful integration of outputs into business processes.

Essential Skills and Experience

2–5 years of experience in data science or a closely related field.


Strong programming skills in Python and PySpark.
Solid data science modelling skills with a problem-solving mindset.
Strong analytical and communication skills, with the ability to tailor complex insights for both technical and non-technical audiences.
Hands-on experience with Databricks for deploying, monitoring, and maintaining machine learning pipelines.
Experience working with AWS data services and architectures.
Good understanding of code versioning and CI/CD tools and practices.

Desirable Skills & Experience:

Familiarity with Databricks Asset Bundles (DAB) for CI/CD and workflow orchestration.


Experience with Harness or similar deployment automation platforms.

The Perks:

25 Days Holiday, with the option to buy up to 10 more, plus 4 flexible bank holidays


10% Company Pension
Annual Bonus Scheme
2 Weeks Work From Anywhere
MediCash Programme
On Site Gym
A Host of Flexible Benefits & Discounts

ED&I at CAVU:


We are an equal opportunities employer. We do not discriminate based on religion, race, colour, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status.


Did you know some people might be less likely to apply for a role unless they meet every single qualification? If you’re excited about this opportunity but your experience doesn’t perfectly match every requirement — we’d still love to hear from you.


If you require reasonable adjustments during the interview process, please contact us so we can accommodate your needs.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

The Future of Machine Learning Jobs: Careers That Don’t Exist Yet

Machine learning (ML) has quickly become one of the most transformative forces in modern technology. What began as a subset of artificial intelligence—focused on algorithms that learn from data—has grown into a foundational capability across industries. From voice assistants and recommendation systems to fraud detection and predictive healthcare, machine learning underpins countless innovations shaping daily life. In the UK, demand for ML professionals has surged. Financial services, healthcare providers, retailers, and tech start-ups are investing heavily in ML talent. Roles like Machine Learning Engineer, Data Scientist, and AI Researcher are among the most sought-after and best-paid in the tech sector. Yet we are still only at the start. Advances in generative AI, quantum computing, edge intelligence, and ethical governance are reshaping the field. Many of the most critical machine learning jobs of the next 10–20 years don’t exist yet. This article explores why new careers will emerge, the kinds of roles likely to appear, how today’s jobs will evolve, why the UK is well positioned, and how professionals can prepare.

Seasonal Hiring Peaks for Machine Learning Jobs: The Best Months to Apply & Why

The UK's machine learning sector has evolved into one of Europe's most intellectually stimulating and financially rewarding technology markets, with roles spanning from junior ML engineers to principal machine learning scientists and heads of artificial intelligence research. With machine learning positions commanding salaries from £32,000 for graduate ML engineers to £160,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this pioneering and rapidly evolving field. Unlike traditional software engineering roles, machine learning hiring follows distinct patterns influenced by AI research cycles, model development timelines, and algorithmic innovation schedules. The sector's unique combination of mathematical rigour, computational complexity, and real-world application requirements creates predictable hiring windows that strategic professionals can leverage to advance their careers in developing tomorrow's intelligent systems. This comprehensive guide explores the optimal timing for machine learning job applications in the UK, examining how enterprise AI strategies, academic research cycles, and deep learning initiatives influence recruitment patterns, and why strategic timing can determine whether you join a groundbreaking AI research team or miss the opportunity to develop the next generation of machine learning algorithms.

Pre-Employment Checks for Machine Learning Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in machine learning reflects the discipline's unique position at the intersection of artificial intelligence research, algorithmic decision-making, and transformative business automation. Machine learning professionals often have privileged access to proprietary datasets, cutting-edge algorithms, and strategic AI systems that form the foundation of organizational competitive advantage and automated decision-making capabilities. The machine learning industry operates within complex regulatory frameworks spanning AI governance directives, algorithmic accountability requirements, and emerging ML ethics regulations. Machine learning specialists must demonstrate not only technical competence in model development and deployment but also deep understanding of algorithmic fairness, AI safety principles, and the societal implications of automated decision-making at scale. Modern machine learning roles frequently involve developing systems that impact hiring decisions, financial services, healthcare diagnostics, and autonomous operations across multiple regulatory jurisdictions and ethical frameworks simultaneously. The combination of algorithmic influence, predictive capabilities, and automated decision-making authority makes thorough candidate verification essential for maintaining compliance, fairness, and public trust in AI-powered systems.