Finance Assistant

Worcester
9 months ago
Applications closed

Related Jobs

View all jobs

Finance Data Analyst (Hybrid) – Excel & Supplier Data

Data Analyst and Systems Implementation Owner

Data Analyst And Systems Implementation Owner

Trainee Data Analyst No Experience Necessary

Data Analyst and Systems Implementation Owner

Data Scientist - New Applications

We are seeking a finance assistant/data entry specialist to support the implementation of a new ERP system. The successful candidate will play a key role in migrating data from existing systems into the new ERP, ensuring accuracy, consistency, and completeness of all data. This is a critical position in the project, requiring a high level of focus and precision during the systems implementation process.

Key Responsibilities:
Data Migration: Enter and validate data from legacy systems into the new ERP system, ensuring accuracy, consistency, and completeness.

Data Cleansing: Review and clean existing data to identify and rectify any discrepancies or errors before migration into the new system.

Data Quality Assurance: Conduct thorough checks and validation of migrated data, identifying any gaps or issues, and working closely with the project team to resolve them.

System Testing: Assist in testing the new ERP system by entering test data, monitoring outputs, and reporting issues or errors encountered.

Documentation: Maintain accurate documentation of data entry procedures, including data mapping and transformation rules for future reference.

Collaboration: Work closely with IT teams, business analysts, and other stakeholders to ensure smooth integration of data into the ERP system.

Data Formatting: Format data according to the ERP system requirements and data standards.

Reporting: Generate reports from the new ERP system for analysis, ensuring the completeness and accuracy of all entered data.

Support: Provide ongoing support during the post-implementation phase, assisting with data-related queries and issues.

Experience in finance is essential and any experience in data entry, data migration, or working with ERP systems (particularly during implementations) is preferred.

This is a temporary role, ongoing for a few months and is based onsite in WR2 5 days a week

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.

Careers Jobs

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.

Jobs

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.

Education Jobs

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.