Junior Project Manager

Warrington
2 weeks ago
Applications closed

Related Jobs

View all jobs

Senior Information Manager

Principal Information Manager

Business Analyst - Assistant Manager

Technical Business Analyst - Assistant Manager

Senior Manufacturing Engineer

Senior Geo-Environmental Engineer

Role: Junior Project Manager

Location: Warrington (Hybrid working after probation)

Salary: £28,000 - £32,000 (DoE)

Are you an early-career Project Manager looking to develop your skills in a fast-paced and supportive IT environment? This is your chance to join a dynamic tech consultancy at I Warrington, delivering real impact across a wide range of client technology projects.

The Role:
As a Junior Project Manager, you'll support the end-to-end delivery of data-focused projects, including business intelligence, data management, and analytics. You'll work closely with senior delivery leads and technical teams to keep projects on track, coordinate resources, and maintain high-quality documentation. You'll be responsible for timelines, reporting, and stakeholder coordination while learning from senior project leads in a collaborative environment that prioritises growth and development.

The client:

Our client is a market-leading technical consultancy in their niche, with a client-base that stretches across the UK and a reputation for delivering innovative data solutions on time, in budget and to a high standard. They've been well established for a number of years and are now expanding the team following a period of growth.

Requirements:

1+ year of experience in a project coordination or junior PM role.
Strong organisational skills and attention to detail.
Excellent written and verbal communication.
Comfortable using collaboration tools like Jira, Zoho, or DevOps.
Interest in data, analytics, or technology-driven environments.
Familiarity with Agile, SCRUM or PRINCE2 (certifications a bonus).
Degree level education.
Full UK driving license.

If you are eager to learn and have strong experience with the skill set above, and the role looks like a great fit, then please send your updated CV to .

Please note: All candidates must have full rights to work in the UK without any current or future requirements for sponsorship.

Role: Junior Project Manager

Location: Warrington (Hybrid working after probation)

Salary: £28,000 - £32,000 (DoE)

In Technology Group Ltd is acting as an Employment Agency in relation to this vacancy

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.