National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Data Scientist

Page Personnel
central belt, scotland
2 weeks ago
Create job alert
A fantastic opportunity to join a growing biotech Developing innovative technology to support diagnosis and biomarker discovery

About Our Client

The client are an innovative biotech developing cutting-edge biosensors for use in diagnostics and biomarker discovery applications.

Job Description

As a Data Scientist you will:

Develop computational models to analyse correlation between test data and performance, supporting with optimisation of products Support the development of a MySQL-based engineering database, integrating real-time sensor and assay performance data Implement multivariate computational models (e.g., Principal Component Analysis (PCA), Partial Least Squares (PLS)) to identify key measurement variables within complex electrochemical datasets. Develop non-linear regression models to improve the accuracy of immunoassay data analysis. Apply machine learning techniques, including Random Forest and neural networks, to classify sample types based on electrochemical measurements, supporting biomarker discovery Design and optimise predictive models to identify novel biomarker panels, combining healthcare data and biomarker signatures. Develop AI-driven classification models to differentiate between patient sub-types based on electrochemical sensor outputs.

The role is site-based in the central belt of Scotland

The Successful Applicant

To be successful in the role you will:

PhD or MSc in Mathematics, Physics or related field Strong experience in computational modelling, data analysis, and machine learning techniques. Proficiency in Python, R, MATLAB, or other statistical programming languages. Knowledge of multivariate analysis techniques (e.g., PCA, PLS) and non-linear regression models. Experience developing predictive machine learning algorithms (e.g., Random Forest, Neural Networks). Proficiency in SQL (preferably MySQL) and database management for engineering data storage Experience working with biomedical data science, bioinformatics or diagnostics is desired but not essential

What's on Offer

This is a fantastic opportunity to join an innovative and growing biotech developing cutting-edge technology.

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist - AI / ML, Python, Scripting, Cyber Security

Data Scientist - Inside IR35 contract

Data Scientist

Data Scientist

National AI Awards 2025

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.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.