Senior Data Scientist

Indeximate
Nottingham
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Indeximate

Indeximate is a rapidly growing VC backed startup focussed on reducing the barriers to net zero using the fantastic wealth of data that can be obtained using fibre optic sensing. We are permanently instrumenting subsea power cables that provide us with our vital electricity supplies and are using this data to reduce the risks of these cables failing.


Our data has a myriad of other uses: monitoring the environment and the weather, mobility of the seabed, tracking marine mammals, detecting vessels and much more. One of our our core goals is liberating these multiple measurements and delivering low cost sensing as a service direct to the desktop. Our existing IP in data compression and analysis is the foundation of this wide future - we are looking for candidates to help us rapidly grow this vision.


What are the role responsibilities?

The role is split between commercially driven R&D into next generation data products and delivering insight to existing customer projects. Your insight will augment our automated workflows by processing vast volumes of data using in-house tools to obtain an understanding of the state of cables and the local environment, providing meaningful output for clients. You will be responsible for assembling and presenting reports both internally and externally. Another key responsibility is the development of algorithms used to extract insight from the data records. This will involve investigating different approaches, developing successful avenues and testing before implementation. Machine learning and alternative data compression techniques are additional topics to be explored in this role.


Key Accountabilities

·         Process Indeximated data from commercial jobs to extract cable health metrics

·         Assemble processed data and interpretation of the data into report format for clients

·         Investigate new methods of extracting useful metrics from the data

·         Check on installations (remotely and in person as needed) and ensure all is running smoothly

·         Present data at conferences and customer meetings

·         Developing machine learning and data compression techniques to improve our product

·         Contribute to the test data set

·         Innovating on behalf of the company


Your Experience & Qualifications

You will be a UK citizen holding a graduate or extended degree in a relevant subject (Data science, Physics, computer science, Maths etc) and have cemented those qualifications with three or more years of experience post degree and can provide a robust portfolio of evidence of your ability to manipulate and process large datasets. Additionally we expect candidates to demonstrate competence in:


·         Understanding of Physics, especially acoustics and acoustic signal propagation

·         Physics based modelling

·         Experience in IP generation

·         Driving Licence


We welcome applications from part time amd full time workers. The role will involve regular low frequency travel.


Your Skills

We are a Physics based data science company and this role is at the deep end of that experience and we expect that candidates will have a good grasp of physics and signal processing, in addition we'd love to hear from candidates with good knowledge & skills in:

·         Demonstrable ability to solve data analysis problems with Matlab, Python or similar

·         Show ability to implement and test new algorithmic concepts

·         Used data compression and machine learning in real applications

·         Good communication and presentation skills – suitable track record to be demonstrated

·         Comfortable with remote working

·         Comfortable with regular travel to meetings (internal and external) and conferences as required


Apply directly to express your interest! We look forward to hearing from you. Apply directly in LinnkedIn and send a covering letter to

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.

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.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.