Digital Project Manager

Collabera Digital
London
1 year ago
Applications closed

Related Jobs

View all jobs

SC Cleared - Data Engineer (Databricks / Azure)

SC Cleared - Data Engineer (Databricks / Azure)

Trainee Data Analyst

Principal Data Engineer

Benefit Risk Management Center of Excellence Data Scientist

Benefit Risk Management Center of Excellence Data Scientist

Description: We are seeking an experienced Digital Project Manager with a strong background in marketing, content management, and new website launches. This role requires a dynamic individual who can seamlessly manage digital projects from concept to completion, ensuring alignment with marketing strategies and business objectives. The ideal candidate will have a proven track record in digital project management, exceptional communication skills, and a passion for delivering high-quality digital experiences. The role involves working within a matrixed organization, requiring effective collaboration across various departments and levels. Key Responsibilities: 1. Project Management: Lead and manage digital projects, including website redesigns, new website launches, content creation, and digital marketing campaigns. Develop detailed project plans, timelines, and budgets, ensuring all projects are delivered on time and within scope. Coordinate with cross-functional teams, including designers, developers, marketers, and content creators, to ensure project milestones are met. 2. Marketing & Content Management: Collaborate with the marketing team to align project goals with overall marketing strategies and campaigns. Oversee the creation and deployment of digital content, ensuring consistency with brand voice and style guidelines. Manage SEO, SEM, and other digital marketing initiatives to optimize website performance and traffic. 3. New Website Launches: Plan and execute new website launches, including managing the migration of content, setting up analytics, and conducting quality assurance checks. Work closely with UX/UI designers and developers to create user-friendly and visually appealing websites. Monitor and analyze website performance post-launch, making recommendations for improvements based on data insights. 4. Matrixed Organization Collaboration: Navigate the complexities of a matrixed organization by working with multiple stakeholders across different departments and levels. Facilitate communication and alignment between various business units, ensuring all parties are informed and engaged. Manage competing priorities and balance the needs of multiple stakeholders to achieve project success. 5. Stakeholder Communication: Serve as the primary point of contact for all project-related communications, providing regular updates to stakeholders. Conduct project meetings, presentations, and workshops as needed to keep all team members informed and engaged. 6. Quality Assurance & Reporting: Ensure all digital projects meet quality standards and business objectives. Track and report on project performance metrics, including KPIs, ROI, and user engagement. Identify and mitigate potential risks throughout the project lifecycle. About Us: Collabera Digital is a Leading Digital Solutions company providing Software Engineering Solutions to the world’s most tech-forward organizations. With more than 25 years of experience, we have hired over 17000 employees across 60 offices globally and currently place 10000 professionals annually to support critical IT engagements at more than 500 client sites, 80% being the Fortune 500. {and 59% of the Fortune 50 (could use either stat)} With Collabera Digital, you: Will get to work on numerous challenging and exciting projects, including Salesforce, AI/Data Science, Generative AI, Automation, Cloud Enterprise, and Cyber Security. At Collabera Digital, you have an 80% chance of project extension or redeployment to other clients. Will have endless opportunities to learn new technologies through our in-house training arm – Cognixia. Additionally, you can also share the CV at ashwini.wanjaricollaberadigital.com of anyone you know who might be a good fit for this position. We have a referral policy in place.

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.

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.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.