Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Graduate Data Scientist

Innovative Technology
Lancashire
4 weeks ago
Create job alert
We are looking for a Graduate Data Scientist

We are looking for a Graduate Data Scientist to work in a fast paced, global, market leading company. Here at Innovative Technology, we have an excellent opportunity for Graduate Data Scientist to join our talented team at our global head office in Oldham, Greater Manchester.


The Graduate Data Scientist role overview:

This role is to maintain and proactively develop Machine Learning algorithms for current and future products, with a core focus on biometric technologies.


Your Responsibilities as a Graduate Data Scientist:

  • Contribute directly to the development, implementation, and validation of Machine Learning algorithms for our industry-leading biometric and face analysis technologies.
  • Optimize and fine-tune existing models, including tuning and retraining existing Convolutional Neural Networks (CNNs).
  • Investigate and resolve underlying system and algorithm issues identified through testing and customer feedback.
  • Drive continuous improvement through research and development of novel techniques in the field.
  • Ensure all code added to the pipeline and shared Git repositories is of the required standard, well‑documented, and easy to maintain.
  • Package all code with appropriate unit‑testing to ensure future conformity and stability.
  • Actively contribute to developing Data Science activities and proposing new processes for quality development (e.g., standard reporting, source control, integration).

Your Skills & Experience:

  • A degree in Mathematics, Computer Science or Computational Science.
  • Basic knowledge of Data Science/Machine Learning algorithms and full data processing pipelines.
  • Proficiency in a Data Science prototyping language such as Python or MATLAB.
  • Understanding of Convolutional Neural Networks (CNNs) and Feature Extraction techniques.
  • Basic knowledge of programming languages including Python, C++, and C, along with libraries such as Scikit‑Learn, NumPy, and/or SciPy.

Your Package & Perks:

  • A competitive salary
  • Flexible working hours
  • 32 days holiday, (including public Holidays) plus the opportunity to earn up to an extra 13 days holiday each year
  • Enhanced maternity/paternity/adoption leave & pay
  • Enhanced Pension Contribution
  • Healthcare Insurance (including dental)
  • Wellbeing support
  • Life Insurance
  • Income Protection Insurance
  • Educational Sponsorship
  • Electric Car Scheme
  • Free secure parking
  • Onsite electric car charging points
  • Cycle to Work Scheme
  • Informal dress code
  • Paid breaks, with free hot premium drinks

You find us on the edge of the Pennines and less than half an hour from central Manchester, with modern offices, free parking and excellent transport links.


We are a disability‑confident employer, as such we will shortlist all candidates meeting our minimum criteria (as specified in the job description) who state they have a disability within their application.


What s next?

If you are looking to join our award‑winning team working on the latest cutting‑edge technology, we want to hear from you.


A better way Through our people, drive and commitment we push boundaries to deliver innovative products and services.


#J-18808-Ljbffr

Related Jobs

View all jobs

Graduate Data Scientist

Graduate Data Scientist

Graduate Data Scientist

Graduate Data Scientist

Graduate Data Scientist

Graduate 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.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.