Master Data Analyst

Chelmsley Wood
2 weeks ago
Create job alert

Purpose

We are seeking an experienced CargoWise Master Data Analyst to oversee the management and governance of

Master Data within our CargoWise freight forwarding software system. The ideal candidate will ensure data

integrity, accuracy, and consistency to support our operational efficiency and decision-making processes.

Candidates will be joining a strong technical team of four focused individuals and contribute to a collective focus

of maximising the optimisation and usage of CargoWise.

Key Accountabilities and Responsibilities:

• Master Data Governance: Establish and enforce policies and procedures for managing Master Data in

CargoWise.

• Data Quality Management: Monitor and ensure the accuracy, completeness, and reliability of Master Data;

implement data cleansing and validation processes. Undertake data entry tasks as and when required.

• Data Integration: Collaborate with IT and operations teams to design, implement, and optimise data

integration workflows between CargoWise and other enterprise systems.

• Training and Support: Provide training and support to users on Master Data management best practices and

the effective use of CargoWise features.

• Reporting and Analytics: Develop and maintain reporting tools and dashboards to track Master Data

performance metrics and inform decision-making.

• System Optimisation: Identify opportunities for process improvements within the CargoWise platform to

enhance Master Data management efficiencies.

• Cross-Functional Collaboration: Work closely with freight operations, finance, and compliance teams to

align Master Data requirements with business objectives. Act as the primary point of contact for day-to-day

Master Data end users (colleagues) for their area of the business providing support for queries and issues,

ensuring timely resolution and escalation when necessary.

• Project Management: Lead or participate in data-related projects, ensuring alignment with organisational

goals and effective execution.

Page 1 of 2[IT & Technical Solutions]

• Research & Project Support: Conduct thorough research on project-related information and compile

concise advisor summaries and notes for distribution. Where required reach out to relevant external

helpdesks to address any inquiries or concerns pertinent to the project.

Desirable Knowledge, Skills

  • Proven experience in data management and governance, preferably within the freight forwarding or

    logistics sector.

  • Understanding of Company Structures and a general awareness of how commercial organisations operate

  • Proactive in approach to the practical implementation of data governance practices

  • Experience of navigating ambiguous situations, displaying strong problem solving and analytical skills with

    the ability to assess complex information, identify key issues and support the reporting of data risks.

  • IT literate, MS Office applications.

  • Proficiency in CargoWise software including modules: Organisations, Contacts, All Reference Files

    (Shipping Lines and Airlines & Vessel Lists), International Zones, Consolidations, Shipments, Customs

    Declarations, Transport Bookings, Running Reports, Reports and Contact, (preferred)

  • Experience with other ERP or logistics systems is a plus e.g. Descartes MacroPoint, SAP Integrated

    Business Planning, Oracle Supply Chain Management (SCM) Cloud, and Descartes Aljex

Related Jobs

View all jobs

Master Data Analyst

Master Data Analyst

SAP Data Analyst

Lead Data Analyst

Data Analyst (HYBRID)

Data Analyst - Portfolio Risk and Analytics

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.

Top 10 Best UK Universities for Data Science Degrees (2025 Guide)

Discover ten of the strongest UK universities for Data Science degrees in 2025. Compare entry requirements, course content, research strength and industry links to choose the right programme for you. Data is the currency of the modern economy, and professionals who can wrangle, model and interpret vast datasets are in demand across every sector—from biotechnology and finance to sport and public policy. UK universities have been at the forefront of statistics, artificial intelligence and large-scale computing for decades, making the country a prime destination for aspiring data scientists. Below, we profile ten institutions whose undergraduate or postgraduate pathways excel in data science. Although league tables vary each year, these universities have a proven record of excellence in teaching, research and industry collaboration.

Veterans in Data Science: A Military‑to‑Civilian Pathway into Analytical Careers

Introduction The UK Government’s National AI Strategy projects that data‑driven innovation could add £630 billion to the economy by 2035. Employers across healthcare, defence, and fintech are scrambling for professionals who can turn raw data into actionable insights. In 2024 alone, job‑tracker Adzuna recorded a 42 % year‑on‑year rise in data‑science vacancies, with average advertised salaries surpassing £65k. For veterans, that talent drought is a golden opportunity. Whether you plotted artillery trajectories, decrypted enemy comms, or managed aircraft engine logs, you have already practised the fundamentals of hypothesis‑driven analysis and statistical rigour. This guide explains how to translate your military experience into civilian data‑science language, leverage Ministry of Defence (MoD) transition programmes, and land a rewarding role building predictive models that solve real‑world problems. Quick Win: Take a peek at our live Junior Data Scientist roles to see who’s hiring this week.

Quantum-Enhanced AI in Data Science: Embracing the Next Frontier

Data science has undergone a staggering transformation in the past decade, evolving from a niche academic discipline into a linchpin of modern industry. Across every sector—finance, healthcare, retail, manufacturing—data scientists have become indispensable, leveraging statistical methods and machine learning to turn raw information into actionable insights. Yet as datasets grow ever larger and machine learning models become more computationally expensive, there are genuine questions about how far current methods can be pushed. Enter quantum computing, a nascent but promising technology grounded in the counterintuitive principles of quantum mechanics. Often dismissed just a few years ago as purely experimental, quantum computing is quickly gaining traction as prototypes evolve into cloud-accessible machines. When paired with artificial intelligence—particularly in the realm of data science—the results could be game-changing. From faster model training and complex optimisation to entirely new forms of data analysis, quantum-enhanced AI stands poised to disrupt established practices and create new opportunities. In this article, we will: Explore how data science has reached its current limits in certain areas, and why classical hardware might no longer suffice. Provide an accessible overview of quantum computing concepts and how they differ from classical systems. Examine the potential of quantum-enhanced AI to solve key data science challenges, from data wrangling to advanced machine learning. Highlight real-world applications, emerging job roles, and the skills you need to thrive in this new landscape. Offer actionable steps for data professionals eager to stay ahead of the curve in a rapidly evolving field. Whether you’re a practising data scientist, a student weighing up your future specialisations, or an executive curious about the next technological leap, read on. The quantum era may be closer than you think, and it promises to radically transform the very fabric of data science.