National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Assistant Data Analyst

Oxford University Press
Oxfordshire
4 days ago
Create job alert

About the Role

Reporting to the Data & Analytics Manager, the Assistant Data Analyst is responsible for supporting the work of the Academic data team by collecting, processing, and analysing data to provide insights to the Academic Sales function. You will work directly with senior analysts and other key stakeholders to gather data requirements and deliver reporting in the context of wider team initiatives.


Responsible for running weekly and monthly reoccurring reports, the role must also be able to provide ad hoc reporting and analysis in line with business demand. You will also be accountable for the thorough documentation of data processes and will adhere to best practices for following data governance policies.


Key responsibilities in this role will include:

Perform basic data analysis using statistical techniques and tools.


Produce ad hoc reports and analysis that are timely and error free, according to business needs.
Assist in creating reports, dashboards, and visualisations to communicate findings effectively.
Collaborate with senior analysts to develop insights that contribute to business strategies.
Collaborate with operational support teams to understand their business needs and data requirements.
Responsible for providing self-serve reporting and automating manual reporting solutions where possible for operational support teams.
Responsible for running regular data updates, monitoring data quality, and resolving data-related issues.
Adhere to data governance standards and follow best practices for data handling and process documentation.
Participate in the data team’s data validation and control processes.
Participate in training and development opportunities to enhance skills and knowledge.

We operate a hybrid working policy that requires a minimum of 2 days per week in the Oxford office. 

About You


To be successful in this role, you will ideally have:

Experience with data manipulation and analysis using tools such as Excel or SQL


Strong attention to detail and problem-solving skills.
Ability to work collaboratively in a team environment
Eagerness to learn and adapt to new technologies and techniques
Effective communication skills, both written and verbal
Familiarity with data visualization (e.g., Power BI, Tableau)
Familiarity with BI tools such as Alteryx (Desirable)
Basic understanding of statistical concepts and methodologies (Desirable)

Benefits


We care about work/life balance here at OUP. With this in mind we offer 25 days’ holiday that rises with service, plus bank holidays and Christmas closure (3-days) and a 35-hour working week. We are open to discussing flexibility in respect to working patterns, dependent on role. We also have a great variety of active employee networks and societies. 


We help make your money go further by contributing to your pension up to 12%, offering loans and savings schemes through our partnership with Salary Finance, in addition to travel to work schemes and access to a wide range of local discounts. 


Please see our Rewards and Recognition page for more information.

Related Jobs

View all jobs

Assistant Data Analyst

Assistant Data Analyst

Legal Onboarding Specialist

Image Data Analyst

Graduate Business Intelligence Analyst (Power BI)

Quantitative Trading Analyst

National AI Awards 2025

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.

Data Science Jobs Skills Radar 2026: Emerging Tools, Languages & Platforms to Learn Now

The UK’s data science job market is evolving fast—from forecasting models and AI assistants to real-time decision systems. In 2026, data scientists aren’t just expected to build models—they’re responsible for shaping insights that fuel everything from patient care to predictive banking. Welcome to the Data Science Jobs Skills Radar 2026—your essential annual guide to the languages, tools, and platforms driving demand across the UK. Whether you’re entering the job market or reskilling mid-career, this roadmap helps you prioritise the skills that matter most right now.

How to Find Hidden Data Science Jobs in the UK Using Professional Bodies like the RSS, BCS & More

The data science job market in the UK is thriving—but also increasingly competitive. As organisations in finance, healthcare, retail, government, and tech accelerate digital transformation, the demand for data talent has soared. Yet many of the best data science jobs are never posted publicly. They’re shared behind closed doors—within professional networks, at invite-only events, or through member-only mailing lists and specialist interest groups. These “hidden” roles are often filled through referrals, collaborations, or direct outreach to trusted experts. In this guide, we’ll show you how to unlock these hidden opportunities by engaging with key UK professional bodies such as the Royal Statistical Society (RSS), BCS (The Chartered Institute for IT), and Turing Society, plus communities like PyData and AI UK. You’ll learn how to use directories, CPD events, and networks to move beyond job boards—and into roles where you’re approached, not just applying.

How to Get a Better Data Science Job After a Lay-Off or Redundancy

Redundancy can be tough to face, especially in a competitive field like data science. But it’s important to know: your experience, analytical thinking, and modelling skills are still in demand. Across sectors like healthcare, finance, e-commerce, government and AI startups, UK employers continue to seek data scientists who can deliver value through insight, prediction, and automation. This guide will walk you through how to bounce back from redundancy with purpose and clarity—whether you're a data analyst looking to step up, a mid-level data scientist, or a machine learning specialist seeking a better-aligned opportunity.