Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Finance Assistant

Worcester
8 months ago
Applications closed

Related Jobs

View all jobs

Finance Data Analyst (Hybrid) – Excel & Supplier Data

Quantitative Analyst – Quantitative Developer

Master and Reference Data Strategy Manager - VP

Commercial and Operations Data Analyst

HR Data Analyst

Head of Data Science

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.

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.