Senior Data Scientist (MLOps)

CV-Library
City of London, City and County of the City of London
12 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Faculty London, United Kingdom
Remote

Senior Data Scientist

Data Idols Farringdon, London, EC1M 4BJ, United Kingdom
£85,000 – £95,000 pa

Senior Data Scientist

Bip Solutions Glasgow, Alba / Scotland, G2 1AL, United Kingdom

Senior Data Scientist

PhysicsX United Kingdom

Senior Data Scientist - Single Cell & Spatial

Relation Therapeutics London, United Kingdom
Permanent

Senior Data Scientist – Computational Genomics

Relation Therapeutics London, United Kingdom
Permanent
Posted
1 May 2025 (12 months ago)

A world class Tech Organisation are looking for a Senior Data Scientist (MLOps) to join their division in London on a hybrid basis - opportunity to join a really innovative environment where you'll work with cutting edge technologies.

The company:

The organisation have been running very successfully now for over twenty years and are recognised as market leaders in their sector. They have a global footprint, and their products are used by millions of users every single day.

They are entering a really exciting period of growth, and are recruiting for a number of new positions to the business as they've got pretty big plans for the next few years - so it's genuinely a great time to join.

They thrive on a positive and welcoming culture making it a great place to work, so it probably comes as no surprise that they have really low attrition rates, as so many of their staff members have long and successful careers with the business.

The role:

You'll be joining a multi-disciplinary Senior squad of roughly 6 consisting of Principle and Senior Software Engineers, Data Engineers and Data Scientists, and will be tasked with supporting machine learning teams with deploying and maintaining models in production, ensuring they are reliable, scalable, and adhere to best practices.

You'll be involved optimizing model performance, mitigating risks, and refining deployment pipelines to meet governance and regulatory standards. You will collaborate with the ML platform team advocating for effective use of tools like feature stores and model registries.

This role acts as the glue between data science and platform engineering teams, fostering MLOps best practices, addressing bottlenecks in inference and retraining pipelines, and resolving production issues to enhance system robustness and cost efficiency.

Key skills and experience:

** Prior Senior Data Scientist with Machine Learning experience

** Strong understanding and experience with ML models and ML observability tools

** Strong Python and SQL experience

** Spark / Apache Airflow

** ML frame work experience (PyTorch / TensorFlow / Scikit-Learn)

** Experience with cloud platforms (preferably AWS)

** Experience with containerisation technologies

Useful information:

Their offices are based in central London where they support hybrid working, you'll be expected onsite about twice a week, however they are really flexible about what days.

They're offering a very competitive salary from £70,000 - £95,000, depending on experience with great benefits to match (which include multiple bonuses and more!).

If you're keen to find out more, please reach out to Matthew MacAlpine at Cathcart Technology

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.

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Advertising machine learning jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.