Senior Data Scientist – NLP & MLOps

Propel London
London
1 year ago
Create job alert

Job Description

As a Senior Data Scientist within the product team, you will bring your expertise to a full stack technology team working to solve Natural Language Processing (NLP) linguistic challenges. The team is product focussed and is developing the world’s leading AI software to provide effortless access to knowledge from real world data and enable customers to make better decisions.

What will you be doing?





We are looking for an experienced Data Scientist with a strong hands on mathematical background and experience in NLP.

You will be developing the best solutions to deliver a roadmap which is aligned to core product features.



Working closely to a product manager to develop new features. The Senior data scientist will be working on projects which continually develop and improve the AI software using the appropriate MLOps tools to deploy, scale and monitor models in production.




What you will bring to the team!





Skills

- Detailed knowledge of AI techniques, including how to train, fine tune and apply deep learning models.
- NLP commercial and research experience and aptitude to continuous learning in this space.
- Experience building Data Science solutions in a commercial environment and the ability to quantify improvements based upon analysis.
- Good awareness of software engineering and coding best practices.
- MSc or PhD - equivalent professional experience in a data science role.



Nice to have skills

- Experience of modern NLP techniques is an advantage.
- Experience of using data science platforms and frameworks, for data tagging, model training and benchmarking.
- Experience building and deploying solutions to the Cloud.
- Experience of the following technologies would be beneficial, Python, Seldon, Helm, Pachyderm, AWS or other cloud technologies, Kubernetes, Docker,
- Knowledge graphs, Graph databases, SQL and Relational databases.
Ability to thrive effectively in predominantly remote working environment.


Why this opportunity over something else?

- Hybrid working model available, Remote first organisation with 90 people based across the United Kingdom.
- The ‘anywhere’ scheme offers you the chance to work wherever you like for part of the year
- Generous holiday package with an opportunity to buy and sell holiday
- Share scheme available for all employees
- £1000 annual training budget - Culture of knowledge sharing with Team Lunch and Learns
- Competitive Pension Scheme


As a Senior Data Scientist you will earn a great package + a range of impressive benefits + share options whilst working fully remote or hybrid in a UK Office.

Related Jobs

View all jobs

Senior Data Scientist

Senior Machine Learning Scientist - Search

Senior Machine Learning Scientist

Western Europe Practice Head - Data Science (Machine Learning/Artificial Intelligence (ML/AI)

Machine Learning Engineer (Manager)

Senior 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.