Science Analytics and Reporting Specialist

Reading
9 months ago
Applications closed

Related Jobs

View all jobs

Business Intelligence Developer

Business Intelligence Developer

Business Intelligence Developer

Business Intelligence Developer - Finance Power BI Specialist

Business Intelligence Developer - Finance / Power BI Specialist

Senior Statistician - HTA

Science Analytics and Reporting Specialist

Location: RG7 4PR, located between Reading and Basingstoke, with free onsite parking.

Package: £47,860 - £70,200 (depending on your suitability, qualifications, and level of experience)

Working pattern: AWE operates a 9-day working fortnight. We will consider flexible working requests so that your work may fit in with your lifestyle. Just let us know your preferred working pattern on your application.

Let us introduce the role

The Science Business Operations team at AWE is committed to driving excellence and innovation in our business processes. We are seeking a motivated individual with a growth mindset to join us as a Science Analytics & Reporting Specialist. This role offers the opportunity to make a significant impact on our reporting and analytics capabilities, supporting key stakeholders in making informed business decisions.

As a Science Analytics & Reporting Specialist, you will collaborate closely with all Science areas to develop delivery performance indicators and ensure effective reporting across all levels of the business. You will coordinate the development and management of reporting and metrics across various aspects of our business operations, including resourcing, finances, and delivery. This role requires regular engagement with stakeholders both within science and across the broader business.

Who are we looking for?

We do need you to have the following:

Proficiency in Microsoft products including Power Automate and PowerApps.

Understanding and experience in data engineering, encompassing ETL processes, data quality, integrity, and security.

Experience with reporting tools such as Power BI.

Experience with EPBVS (Enterprise Planning & Budgetary Cloud Service).

Strong proficiency in SQL and other data querying languages.

Proven analytical and critical thinking skills, with the ability to interpret complex data and present findings to a diverse audience

Everyone who works at AWE brings unique skills and perspectives to the table. We recognise that great people don't always 'tick every box'. That's why we focus on your potential, your fit with our values, your transferable skills as well as your experience. Even if you don't meet every point below, but you feel that this role and AWE are a great fit for you, please go ahead and apply, we'd love to receive your application.

Whilst not to be considered a tick list, we'd like you to have experience in some of the following:

Managing a diverse range of stakeholders, including senior leadership/stakeholders as customers

Growth mindset with a proactive approach to seeking opportunities for continuous improvement and efficiencies

Excellent written and verbal communication skills, with the ability to present complex information clearly and concisely to various audiences.

Understanding and experience with Data Science, including development and implementation of advanced analytics models, such as machine learning and statistical models

Knowledge of Palantir Foundry and its data integration and analytics capabilities

Understanding of how to present metrics and management information

Project management experience, with the ability to manage multiple projects and deadlines simultaneously

Some reasons we think you'll love it here:

AWE has wide range of benefits to suit you. These include:

9-day working fortnight - meaning you get every other Friday off work, in addition to 270 hours of annual leave.

Market leading contributory pension scheme (we will pay between 9% and 13% of your pensionable pay depending on your contributions).

Family friendly policies: Maternity Leave - 39 Weeks Full Pay and Paternity Leave - 4 Weeks Full Pay.

Opportunities for Professional Career Development including funding for annual membership of a relevant professional body.

Employee Assistance Programme and Occupational Health Services.

Life Assurance (4 x annual salary).

Discounts - access to savings on a wide range of everyday spending.

Special Leave Policy including paid time off for volunteering, public service (including reserve forces) and caring.

The 'Working at AWE' page on our website is where you can find full details in the 'AWE Benefits Guide'.

Important things you need to know:

You will need to obtain and maintain the necessary security clearance for the role. This will be funded by AWE. The nature of our work does mean you need to be a British Citizen who has been resident in the UK for the past 5 years in order to apply for SC clearance and 10 years for DV.

We want you to feel comfortable and able to shine during our recruitment process. Please let us know on your application form if you need any adjustments/accommodations during the process.

Our interviews typically take place over Teams and for most roles are a 1 stage process.

IF HYBRID POSSIBLE:

Hybrid working is available for this role on an informal, non-contractual basis. Typically 2 days onsite per week.

#LI-DS

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.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

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.