Accounts Assistant

Guildford
11 months ago
Applications closed

Related Jobs

View all jobs

Business Data Analyst

Purchasing Data Quality Support Assistant

Quantitative or Integrated Research Manager

Quantitative or Integrated Senior Research Executive

Data Quality Coordinator

Vendor Master Data Analyst

Accounts Assistant

About the Accounts Assistant Role

The Accounts assistant at Talogy is a core contributor who supports the end-to-end accounts receivable process, providing accurate and timely processing of invoices distribution, collections, and customer account reconciliations. This role is primarily focused on accounts receivable and banking, however this role will also provide cover to other areas such as accounts payable. It’s preferred that this role is French-speaking as they will be required to work closely with various departments both internally and externally within both the UK and France.

This role is a full-time permanent position, (Apply online only), Monday to Friday, although flexible working hours would be considered on request. This role can be performed remotely, however proximity to our Guildford office is preferred so that working from the office can be done on a regular basis (eg once a week).

Accounts Assistant Role Responsibilities

The Accounts assistant role is primarily responsible for:

  • Sales invoicing
    - Prepare and issue sales invoices to customers promptly, liaising with the internal teams to ensure that the billing is complete and on time.
    - Updating/Maintaining the CRM with the relevant invoicing information.
    - Collating information and raising monthly or ad-hoc expenses invoices to specific clients
    - Setting up new clients on the system and ensuring all documentation with is provided and correct.

  • Credit Control – Monitor and chase overdue payments from customers.

  • Respond to and resolve queries relating to customer inquiries regarding invoices, statements, and payment-related issues in an accurate and timely manner.

  • Reconciliations of bank accounts and updating daily cash reports.

  • Provide cover to the accounts payable team when required.

  • Perform general finance administrative tasks, such as roll forward of excel spreadsheets for weekly bank and cash reporting

  • Assist with collating information for the external auditors as requested.

  • Undertake other ad-hoc duties as required

    Accounts Assistant Knowledge, Skills and Experience Requirements

    Essential:

    · Proficient in French

    · At least one year experience of data entry within a finance team or in an administrative role

    · Attention to detail

    · Good MS Excel and Word skills

    · Good communication skills with internal and external individuals

    · Excellent organisation and time management skills

    · Ability to demonstrate working to deadlines successfully

    Desirable:

    · Use of accounting system NetSuite.

    Benefits

    Talogy offers a variety of competitive workplace benefits, including financial planning support, time off benefits, employee assistance programs, medical cover and participation rewards. We have a vibrant social culture, and we provide opportunities for employees to engage in volunteering and charity activities.

    About Talogy

    We are Talogy. The talent management experts. We craft solutions that screen, select, develop, and engage talent worldwide. By uniting the leading psychologists, data scientists, developers, and HR consultants we bring the power of psychology and technology together so you can make the best data-driven people decisions. With more than 30 million assessments delivered each year in more than 50 languages, we help clients discover organizational brilliance

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.

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.

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.