GenAI Data Scientist

MBDA Missile Systems
Bristol
8 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist (GenAI)

Senior Data Scientist (GenAI)

Senior Data Scientist (GenAI)

Senior Data Scientist (GenAI)

Senior Data Scientist (GenAI)

Pricing Data Scientist — GenAI & ML, Hybrid Role

As a generative AI-focused Data Scientist specialising in Natural Language Processing (NLP), you will drive innovation by designing and enhancing cutting-edge AI algorithms tailored for our diverse internal customer. Your primary mission is to empower our teams with maintainable and robust NLP solutions, fostering a data-driven culture throughout the organization.

Salary: Circa £50,000 depending on experience

Dynamic (hybrid) working: 2 days per week on-site due to workload classification

Security Clearance: British Citizen.

Restrictions and/or limitations relating to nationality and/or rights to work may apply. As a minimum and after offer stage, all successful candidates will need to undergo HMG Basic Personnel Security Standard checks (BPSS), which are managed by the MBDA Personnel Security Team.

What we can offer you:

  • Company bonus: Up to £2,500 (based on company performance and will vary year to year)
  • Pension: maximum total (employer and employee) contribution of up to 14%
  • Flexible working: We welcome applicants who are looking for flexible working arrangements
  • Enhanced parental leave: offers up to 26 weeks for maternity, adoption and shared parental leave -enhancements are available for paternity leave, neonatal leave and fertility testing and treatments
  • Facilities: Fantastic site facilities including subsidised meals, free car parking and much more...

The opportunity:

Within MBDA's IM department, we seek a NLP Data Scientist who can architect and code algorithms that harness the power of our internal data. Your role is pivotal in understanding and catering to the unique needs of our internal clients engaged in critical missions such as missile design, weapon systems engineering, IoT integration in manufacturing, and more.

Your responsibilities will encompass the full spectrum of the data science lifecycle: from data exploration and cleaning to algorithm design and implementation, ensuring these algorithms are production-ready and future-proof. Additionally, you will steer our technology roadmap through meticulous tech scouting, delivering state-of-the-art solutions to our internal stakeholders, and keeping our organization at the forefront of innovation.

It is a good opportunity to take part in shaping the future of GenAI within MBDA with your insights and experiences in this newly formed international team.

Key Responsibilities:

  • Capture internal client needs and requirements across diverse business functions.
  • Employ NLP techniques to extract and clean data, ensuring relevance and accuracy.
  • Design and develop algorithms with a focus on NLP, applying the latest LLM and RAG technologies.
  • Validate algorithm performance and complexity against business needs, ensuring durability and responsiveness.
  • Collaborate with internal clients to understand and deliver on their unique data challenges.
  • Stay abreast of the latest advancements in generative AI and NLP, guiding our technology strategy.
  • Ensure smooth data flow through various exchange and processing techniques (ETL, ESB, API).
  • Lead the way in delivering Agile methodologies for successful and timely project delivery.
  • Leverage strong database skills (SQL, NoSQL, and Parquet) for efficient data storage and management.

What we're looking for from you:

  • Proficiency in Data Science techniques, including statistical models and ML algorithms.
  • Expertise in NLP, with a keen understanding of LLM and RAG technologies.
  • Strong development capabilities, particularly in Python.
  • Experience with data exchange, processing, and storage frameworks (ETL, ESB, API, SQL, NoSQL, and Parquet).
  • Comfort with Agile development methodologies.
  • Excellent teamwork and communication skills, with a talent for translating technical concepts into actionable insights for non-specialists.
  • Ability to influence company decision-makers and stakeholder engagement.
  • Flexibility to travel to MBDA European sites when needed

Skills Preferable to Have:

  • Experience with containerization technologies (Docker).
  • Knowledge of the industrial or defence sectors.

Our company: Peace is not a given, Freedom is not a given, Sovereignty is not a given

MBDA is a leading defence organisation. We are proud of the role we play in supporting the Armed Forces who protect our nations. We partner with governments to work together towards a common goal, defending our freedom.

We are proud of our employee-led networks, examples include: Gender Equality, Pride, Menopause Matters, Parents and Carers, Armed Forces, Ethnic Diversity, Neurodiversity, Disability and more...

We recognise that everyone is unique, and we encourage you to speak to us should you require any advice, support or adjustments throughout our recruitment process.

Follow us on LinkedIn (MBDA), X (@MBDA_UK), Instagram (MBDA_UK) and Glassdoor or visit our MBDA Careers website for more information.
#J-18808-Ljbffr

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 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.

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

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.