Product Manager

Noir
Cannock
11 months ago
Applications closed

Related Jobs

View all jobs

Product Manager - Machine Learning

AI Product Manager - Data Science

Machine Learning Engineer

AI Engineer / Data Scientist - Production ML & OCR

Pricing Optimisation Data Scientist

Lead Machine Learning Engineer

Product Manager


Product Manager – Cannock


(Key skills: Product Manager, Software, Stakeholders, Roadmap, Functional Requirements, User Stories, Business Analyst, Project Manager, Product Manager)


I’m currently recruiting on behalf of my client, an innovative leader in digital solutions and insurance technology, looking for an experiencedProduct Managerto join their growing team. This is a fantastic chance to play a pivotal role in driving product strategy, collaborating closely with development teams, and staying on top of cutting-edge advancements in artificial intelligence and machine learning.


The Role:


As the Product Manager, you’ll be responsible for steering product development from concept through to launch, working alongside software development teams to bring innovative, high-quality solutions to market. You’ll utilize your skills in process mapping, business process reengineering, and Agile methodologies to streamline development, staying on top of market trends and AI applications that can transform the industry.


Key Responsibilities:


  • Collaborate with cross-functional teams to oversee the entire product lifecycle.
  • Analyse market trends and customer needs, translating insights into strategic product opportunities.
  • Engage in process mapping and reengineering to enhance product development.
  • Drive Agile product development processes, ensuring efficient, timely releases.
  • Maintain a strong focus on AI and machine learning advancements, identifying potential applications.


What We’re Looking For:


Education and Experience


  • Bachelor’s degree (or higher) in Business Administration, Computer Science, or a related field.
  • Proven experience in product management, ideally within digital solutions, software, or insurance.
  • Strong experience working with software development teams, familiar with SDLC and Agile methodologies.
  • Interest in AI and machine learning, and experience with related tools.
  • Experience with process mapping and business process reengineering.


Technical Skills


  • Proficiency in business analysis tools and techniques.
  • Knowledge of development languages and frameworks (e.g., Java, Python, .NET).
  • Familiarity with AI/ML platforms and process mapping tools like Lucidchart.
  • Strong analytical and problem-solving skills.


What’s on Offer:


This is a unique opportunity to join a company that values innovation and customer-centric solutions. If you’re results-oriented, passionate about technology, and ready to make an impact, this could be the perfect role for you.


Our client is building a company people love.A company that will stand the test of time. So they invest in their people, and optimize for your long term happiness. If you would like to explore the possibility of joining their family please apply without delay.


Location:Cannock, UK / Remote Working


Salary:£45,000 - £60,000 + Bonus + Pension + Benefits


Applicants must be based in the UK and have the right to work in the UK even though remote working is available.


NOIRUKTECHREC

NOIRUKREC

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.