Data Scientist - MRO AI Solutions

hays-gcj-v4-pd-online
Longford
3 weeks ago
Create job alert

Data Scientist – MRO AI Solutions

Role PurposeThe Data Scientist will develop advanced models and analytics to unlock value frompany operational data while ensuring solutions can be adapted for other OpCos. This role requires consultancy-level expertise in AI/ML and a strong ability to translate insights into business impact.
Key Responsibilities

Design and implement predictive and prescriptive models for MRO AI Solutions. Perform exploratory data analysis and feature engineering. Collaborate with Data Engineers to ensure data readiness for modeling. Continuously improve models based on feedback and operational performance. Develop models and analytics that can be generalized and adapted for different OpCos without extensive rework.

Required Skills & ExperienceProficiency in Python and ML frameworks (TensorFlow, PyTorch).Strong statistical and analytical skills.Experience with a wide range of Data Science techniques ( ML, Optimisation, Simulation, GenAI, etc.).Demonstrated ability to take models from design through to production deployment, including performance optimization, monitoring, and integration into business workflows beyond proof-of-concept or prototype stages.Familiarity with airline operations or supply chain analytics is desirable.Significant experience in similar roles, with a proven ability to integrate quickly into new teams and deliver immediate value.Initial co-location with BA teams in London is essential to ensure close collaboration. Candidates must also be prepared to travel internationally during later stages to facilitate group-wide deployment.Preferred Consulting-LevelpetenciesAbility to frameplex problems and deliver actionable solutions.Strong presentation and storytelling skills for executive audiences.Experience in high-impact consulting or transformation projects.Track record of creating high-impact oues and driving stakeholder satisfaction from day one.Experience in building reusable AIponents and frameworks for enterprise-scale deployments.Premium-level role;petitive rates aligned with UK consultancy benchmarks.

#4752865 - Nasar Ali

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

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.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.