Lead Data Scientist – Next Generation Optical Sensing Solutions

Altium Associates
Manchester
4 days ago
Create job alert

Our client is a highly ambitious UK deep-tech venture in rapid expansion mode. The company’s innovative technology offers both a leap in performance and superior power efficiency to create future optical spectroscopy solutions across a number of industry sectors.

To be considered for this newly created role, you will be able demonstrate the following:

  • Proven expertise in spectroscopy, optical sensing, or closely related domains (e.g., NIR/SWIR, chemometrics, or hyperspectral imaging), ideally applied in commercial or applied R&D environments.
  • Strong programming capability in Python and/or MATLAB, with hands-on experience building, validating, and deploying machine learning models using libraries such as PyTorch or TensorFlow.
  • Practical experience applying statistical and machine learning techniques such as PCA, PLS, clustering, anomaly detection, and supervised classification to real datasets.
  • Evidence of building end-to-end data pipelines, including data acquisition, preprocessing, feature engineering, model development, and performance evaluation.
  • Track record of customer-facing or stakeholder-facing technical work, including translating complex technical concepts into clear, actionable insights for non-expert audiences.
  • Demonstrated ability to validate models rigorously, including handling trade-offs (e.g., false positives vs false negatives), assessing dataset sufficiency, and managing bias and generalisation risks.
  • Experience contributing to an early-stage or start-up environment showing adaptability, ownership, and the ability to operate effectively in dynamic environment.

For a confidential discussion and further information about this unique opportunity please contact, Parm Flora, Managing Partner at Altium Associates.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Scientist 4

Principal Machine Learning Engineer

Data Scientist Manager

Data Scientist Senior Consultant - Belfast

Data Scientist Consultant

Lead Data Scientist / Deep Learning Practitioner

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.

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.

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.