Delivery Manager

Healthy.io
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior MLOps Engineer

Senior AI Delivery Manager — Azure & MLOps Lead

Credit Risk Data Science Manager

Technical Program Manager - Machine Learning - New York

Technical Program Manager - Machine Learning - New York

Product Manager - Machine Learning

About the position

Healthy.io is one of the first companies to successfully turn a smartphone into a clinical-grade medical device enabling faster treatment and improved care for patients worldwide. Our products are powered by computer vision and machine learning and create new clinical pathways through smartphone-powered urinalysis and digitized wound management.

We are looking for a Delivery Manager to join our team as we scale our digital wound management service in the UK to support clinicians and transform wound care for patients living with chronic wounds. 

This is an ideal role for recently qualified project managers and or trainers, full product training will be provided and there will be opportunity for growth and development within the company as we scale. We need a highly organised, personable candidate who is able to adapt quickly to different situations and enjoys helping end users and project leads to get the best use of our product. You will enjoy travelling for work and will have a strong work ethic in order to provide exceptional customer service.

Reporting to our Senior Delivery Manager, you will primarily be responsible for supporting the direct deployment of our products including project management of deployment and end user training. We see this as a great role for a highly organised target driven individual who is eager to learn and build their career in digital healthcare, with lots of opportunities for development and taking on additional responsibilities.

Requirements

Highly organised, with attention to detail Excellent knowledge of the NHS Experience delivering services to the NHS or driving uptake of a commissioned service in a healthcare setting Target driven and organised and enthusiastic about the potential for digital healthcare tools to transform care for patients Exceptional written and verbal communication skills, with the ability to articulate complex instructions to different audiences Empathetic and collaborative in approach, with the ability to quickly develop strong relationships Energetic, flexible, and adaptive, able to roll up your sleeves and learn on the job Problem solver, able to think of solutions outside the box Ready to travel for onsite visits across the U.K, full UK driving licence

Role & Responsibilities

Train the support desk team and training support on all new features and deliver effective, high quality training Articulate clearly the value of our service to a range of different audiences Project manage deployment of our product across different types of client profiles  Build strong client relationships with the project team Work closely with our product and operations team to onboard new partners and ensure excellent service provision  Closely monitor user adoption of the service in your assigned accounts  Identify and escalate risks to service delivery.  Contribute to the development of processes and utilisation of tools to speed up project mobilisation and meet partner objectives  Capture product feedback Support the testing and embedding of new features Support the identification and production of case studies

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.

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

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.