SC Cleared Data Scientist

Bassaleg
1 year ago
Applications closed

Related Jobs

View all jobs

Generative AI Data Scientist — Remote (SC Cleared)

Generative AI Data Scientist — Remote (SC Cleared)

Generative AI Data Scientist — Remote (SC Cleared)

SC Cleared Data Engineer – Data Migration (AWS) - Outside IR35

SC Cleared Data Engineer: Databricks on Azure (Remote)

Data Engineer - Central Gov - SC Cleared

SC Cleared Data Scientist
£25.36 per hour / £187 per day
INSIDE IR35
12 Month contract
Full Time - 37 hours per week
Hybrid - 2 to 3 days per week in either Newport, South Wales, Titchfield, Hampshire or Darlington.

My client are a large prestigious government organisation and are looking for an SC Cleared Data Scientist to come and join their team on an initial 12 month basis, paying a hourly/daily rate, inside IR35.

LIVE SC CLEARANCE IS HIGHLY DESIRABLE FOR THIS ROLE

Essential requirements of role:

Proficiency in Python and experience with the full data science and machine learning stack.
Strong software engineering skills with a focus on building robust, production-ready systems and understanding of deploying and monitoring such systems in a cloud environment.
Experience in using data science techniques (e.g. natural language processing, supervised and unsupervised machine learning, deep learning).
Passion for building AI tools that can be used by others to deliver business outcomes.
Successful candidates will be required to undergo SC Clearance, therefore applicants must of resided in the UK for a minimum of five out of the last five years, in order to undergo this level of security check

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.

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.