Digital Development Manager

Ipswich
10 months ago
Applications closed

Related Jobs

View all jobs

Analytics Specialist with Data Science

Data Engineering Manager

Data Engineering Manager

Machine Learning Engineer (Manager)

Machine Learning Engineer (Manager)

Machine Learning Engineer (Manager)

Software Development Manager - Pioneering Tech Innovation I'm working with a market-leading manufacturer based in Ipswich seeking a Software Development Manager to drive their digital transformation journey. This is a brand-new position created to spearhead innovation across the business.

The Role Reporting to the Head of IT, you'll combine strategic leadership with hands-on development expertise to deliver cutting-edge digital solutions while building a high-performing team.

Key Responsibilities:
Lead the application support team, managing workloads and day-to-day operations
Contribute directly to development tasks, ensuring high-quality technical solutions
Implement and maintain robust development processes and secure lifecycles
Identify opportunities to enhance the digital portfolio through innovation
Oversee Power BI development and administration
Establish comprehensive data and reporting strategies
Develop clean, efficient, maintainable code
Introduce low/no-code solutions to optimize the Microsoft stack
Ensure seamless integration between digital platforms and core systemsWhat My Client Needs
Proven experience in UI design, secure applications, and database management
Understanding of complex RESTful web APIs
Leadership experience in digital development roles
In-depth knowledge of web technologies (HTML5, CSS, HTTP, JavaScript, PHP, .NET)
Extensive Microsoft Power Platform expertise (Apps, BI, Automate, Dataverse, Fabric)
Strong grasp of emerging technologies, AI, and machine learning
Familiarity with agile methodologies
Knowledge of CRM/ERP systems and Microsoft Azure/cloud technologies
Previous team management experience with mentoring abilitiesThe Ideal Candidate
Confident and engaging with a positive, proactive approach
Strong leadership skills with excellent communication abilities
Highly proactive with impressive problem-solving capabilities
Excellent time management and prioritization skills
Ability to navigate IT governance, controls and risk managementPackage Details
Competitive salary based on experience
Annual performance bonus
Comprehensive benefits including life assurance and healthcare
Excellent pension scheme
20 days annual leave (increasing to 25 after 1 year)
Extensive development and wellness programmesWorking Arrangements
Full-time, permanent position
Ipswich, Suffolk location with hybrid working options after probationIf you're a tech leader passionate about driving digital transformation in a collaborative, fast-paced environment, I'd love to discuss this opportunity with you

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.

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.

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

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.