Operations Data Analyst

Liverpool
1 hour ago
Create job alert

Operations Process Analyst

Red Recruitment is looking to recruit a Operations Data Analyst for our client. You will be responsible for all aspects of the development, implementation and maintenance of the data analysis tools & visualisations within the Investment Operations team.

This will also include identifying improvements in existing processes and maintaining all documentation, to ensure a robust business continuity environment.

Benefits and Package for a Operations Data Analyst:

Salary: Competitive

Hours: Full-time

Contract Type: Permanent

Location: Liverpool

25 days annual leave plus bank holidays

Workplace Pension

Private medical insurance for employees

Permanent health insuranceKey Responsibilities of a Operations Data Analyst:

The creation and provision of timely and accurate management information for Investment Operations processes, and their related analytical interpretation across the team.

* The production of data visualisation tools and dashboards to make large or complex data more accessible to the business.

* To use all available tools and packages to introduce rigid, controlled and automated analysis of Wealth at Work and third-party data.

* To ensure that all current and future controls are documented both for their purpose as well as their creation and maintenance.

* To provide trend analysis to meet business needs and provide essential information to feed into the future development and evolution of the team.

* To design and implement controls to ensure that both internal and external Service Level Agreements are met.

* To maintain a good working knowledge of Wealth at Work systems & technical developments.

* To identify and introduce methods to update, simplify and enhance reporting processes, procedures and controls.

* To analyse and integrate new data sets from current or future third party suppliers.

* Being passionate and demonstrate behaviours in line with the Company's ethos, vision and key principles

Key Skills and Experience of a Operations Data Analyst:

Experience demonstrating and publishing dashboards and handling user feedback is essential.

Familiarity with Github and project management tools like Trello and Figma is desirable.

Ability to review & cleanse data sets by identifying corrupted data, fixing coding errors as well as related problems

An analytical approach to risk mitigation and control with an understanding of the role that data analysis plays in automated controls.

Experience of writing and maintaining high-quality business, process and procedural documentation

Comfortable taking responsibility to drive and deliver initiatives from outset to completion

Ability to make recommendations for business and process improvement

Be able to work to deadlines and have proven time management skills

Proactive, collaborative, methodical and thorough approach to work, with excellent attention to detail

Ability to work independently and as part of a team If you are interested in this position and have the relevant experience required, please apply now!

Red Recruitment (Agency)

Related Jobs

View all jobs

Operations Data Analyst

Data Analyst - Sales Operations

HR Data Analyst

Data Analyst

Data Analyst

Data Analyst

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.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.