Senior Data Scientist - Medical/Clinical Informatics

Veritone Hire Programmatic
UK
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

As the Senior Data Scientist - Medical/Clinical Informatics, you will work as part of a broader Data Science team in collaboration with Product and Engineering to deliver solutions focused on improving quality and efficiency of care delivery in the context of hospital-level care at home. You will play a crucial role in improving healthcare delivery and patient care by leveraging data science and informatics expertise. Remote based in the UK . What you'll do Collaborate closely with other disciplines, including IT, biomedical engineering, software engineering, data engineering, and clinical experts Apply a range of data science techniques ranging from AI/machine learning to statistics to data visualization in the context of clinically oriented use cases Partner with data engineers to ensure that data are cleaned, processed, harmonized, and curated in alignment with industry standard practices Work as part of a cross-functional team to integrate predictive models into virtual hospital (e.g., clinical practice, care coordination) workflows Serve as a thought partner and informatics subject matter expert to clinicians and product managers during the ideation and design of new solutions that incorporate data/AI Basic qualifications 3 years of relevant experience with Bachelor's degree in Data Science, Health Informatics, or related field OR equivalent relevant professional experience Preferred qualifications Master's degree in Health Informatics, Medical Informatics, or Clinical Informatics, OR clinical practice experience Significant experience working with healthcare data from hospitals/care delivery/electronic health records Demonstrated experience: AI/machine learning, ranging from more traditional approaches to deep learning/LLM Python, specific to data science (e.g., TensorFlow, PyTorch, scikit-learn, etc.) FHIR, clinical terminologies (ICD-10, CPT, LOINC, etc.), and terminology/value set management systems SQL and NoSQL databases (e.g., document, graph) Cloud environments (e.g., AWS, Snowflake, Databricks) Prototyping and delivering incrementally, focusing on good science, while being agile and iterative based on customer needs Architecting hospital and clinically oriented data science solutions Pragmatic balance of quality with a fast-paced schedule Team player, ready to help, debate, compromise, and work together Ability to: Dive deep into technical details while maintaining a holistic view of the broader context Work within a geographically distributed team (US/UK) What's in it for you We're committed to helping our people thrive at work and at home. We offer generous benefits that address your total well-being and provide support as you need it, especially key moments in your life. Our benefits include: Competitive pay Generous employee discount Physical and mental well-being support About us Best Buy Health aims to enrich lives through technology and meaningful connections. We do that by focusing on consumer health products that help people live healthier lives, device-based emergency response services for the active aging population and virtual care offerings that help connect patients to physicians. Position Type: Full timePandoLogic. Keywords: Data Scientist, Location: London, ENG - SE25 5PY

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.

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.

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.