Product Manager - Data infrastructure & Analytics

CM Medical Recruitment
Sheffield
11 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist: Causal Analytics for Marketing AI

AI Engineer / Data Scientist - Production ML & OCR

Pricing Optimisation Data Scientist

Senior Data Engineer, SQL, RDBMS, AWS, Python, Mainly Remote

Marketing Data Analyst / Scientist - Fintech

Senior Data Engineer, SQL, RDBMS, Python, Celery, RabbitMQ, Pt Remote

CM Medical is exclusively partnered with a leading provider of medical imaging AI solutions. Our partner offers healthcare customers the broadest portfolio of imaging AI solutions via a tried-and-tested platform, seamlessly integrated with customer systems. This platform simplifies the implementation and management of imaging and operational AI applications, enabling efficient addition of new applications to reduce implementation time, costs, and long-term maintenance efforts.


As the Product Manager for Data Infrastructure & Analytics, you will play a pivotal role in supporting the launch of new customer capabilities by leading the development and implementation of data storage, processing, querying, and visualization infrastructure for AI data and analytics across the platform. Your focus will be on transforming vast datasets into actionable insights, which help improve clinical workflows, patient outcomes, and drive AI adoption in healthcare.


Key Responsibilities:


  • Develop & Maintain Data Infrastructure Requirements:Ensure the infrastructure supports AI data storage, processing, querying, and visualization to meet customer and business needs.
  • Drive the Product Roadmap:Contribute to and execute on the product roadmap for data and infrastructure products, aligning with broader strategy and goals. Look for opportunities to deliver incremental value quickly by scoping initiatives efficiently.
  • Collaborate Across Teams:Work closely with stakeholders, including healthcare providers, platform partners, clinicians, data scientists, and software developers, to design and implement scalable solutions that meet technical and regulatory requirements.
  • Manage Product Development:Lead the product development lifecycle from concept to launch, ensuring that performance, scalability, and security standards are met.
  • Ensure Balanced Prioritization:Make well-balanced prioritization decisions, considering multiple perspectives and data points, to ensure product success and alignment with business needs.
  • Track Product Performance:Use analytics and metrics to track product performance, identifying opportunities for improvement and enhancement of data infrastructure and analytics capabilities.
  • Compliance & Security:Maintain awareness of best practices for data security in healthcare and comply with information security requirements outlined in the company’s security manuals.
  • Customer Engagement:Conduct customer interviews, gather feedback, and adjust the product strategy based on clinical workflows and user experiences to ensure alignment with customer needs.


Key Requirements:


  • Technical Expertise in Data Infrastructure:Hands-on experience with data infrastructure technologies, including storage, processing, querying, and visualization tools.
  • Knowledge of Database Systems & Data Models:Strong understanding of database systems, data models (e.g., IHE SOLE, OMOP), and industry standards for healthcare.
  • Proven Product Management Experience:Experience in healthcare technology, clinical informatics, or medical imaging informatics, with demonstrated proficiency in roadmap development, stakeholder management, and product lifecycle management.
  • Proficiency in Data Analytics Tools:Familiarity with data analytics tools and visualization platforms to support decision-making and product performance tracking.
  • Customer-Centric Focus:A strong commitment to engaging with customers, including clinicians and healthcare providers, to refine product strategies based on real-world usage and feedback.
  • Compliance & Regulatory Knowledge:Experience working with healthcare regulatory bodies and understanding industry standards and security requirements for healthcare applications.


Qualifications:


  • Bachelor’s degree in a relevant field (e.g., Computer Science, Engineering, Healthcare Informatics) or equivalent practical experience.
  • Experience in product management, especially in healthcare technology, medical imaging, or clinical informatics.
  • Strong communication skills with the ability to engage and influence a variety of stakeholders.

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.

Jobs

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

Education Jobs

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

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.

Jobs

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.