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

Apply Now

Senior Data Scientist

Morson Talent
London
10 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist - Earth Observation - Energy Aspects

Senior Data Scientist

Senior Data Scientist

Join an industry leader in technology as a Data Scientist, where your expertise will be pivotal in transforming experience for users worldwide. Our client prides itself on innovation, and they are seeking their first Senior Data Scientist to push the boundaries of their cutting-edge technology. This role presents an exciting opportunity for those passionate about technology and the future. Role Responsibilities   As a Data Scientist, you will play a crucial role in advancing our client's revolutionary computer vision software: - Collaborate with the CPO and Head of Engineering to drive the development of technology. - Utilise MediaPipe and MoveNet for pose estimation, creating rules and algorithms to accurately assess workout metrics. - Conduct statistical analysis to minimise inaccuracies, especially in complex scenarios. - Partner with QA to detect, resolve, and prevent bugs in new and existing features. - Coordinate with Customer Support and Marketing to ensure seamless feature integration and user satisfaction. About You   - Extensive experience in a data scientist role within start-up or high-growth environments. - Strong knowledge of MediaPipe, MoveNet, and similar machine learning models, with a focus on pose estimation. - Ability to apply linear algebra, geometry, and statistical methods to solve challenging problems. - Excellent communication skills, particularly when explaining complex technical concepts to non-specialists. About the Company   Our client is a well-established organisation renowned for its pioneering approach in the technology sector. Their innovative solutions, including interactive hologram mirrors and real-time correction software, have earned them accolades and notable exposure in prestigious outlets and industry lists. With a commitment to revolutionising the industry through technology, they continue to attract substantial venture capital investments from prominent funds and individuals. Perks and Benefits   - Competitive salary and share options, reflecting the importance of your contribution. - Unlimited holiday with a self-directed time off policy, promoting work-life balance. - Flexible working arrangements with the option for home or hybrid working. - A hardware budget for the latest technology tools, including a new MacBook or equivalent. - Opportunities for professional learning, development, and regular social events to connect with team members. Next Steps   If you are driven by innovation and eager to make an impact as a Data Scientist, we encourage you to apply. This is your chance to shape the future of technology with a dynamic team and grow with a company that values your input from day one. Seize this opportunity to make your mark in the industry today

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.

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

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.