French Speaking Finance Analyst

Manchester
4 days ago
Create job alert

Junior IT Support Engineer
ABOUT PRGX
We provide the business intelligence to unlock incremental value from data and expand impact across our clients' organizations for healthier whole businesses. PRGX pioneered Recovery Audit nearly 50 years ago and is now the global leader in source-to-pay analytics and margin expansion. PRGX empowers clients in more than 30 countries with the business intelligence to recover $1.2 billion in annual cash flow, unlocking value and improving the overall health of organizations across the world. We collaborate with supplier communities to realize improved profits and deliver the tools to optimize processes, finding immediate and lasting value.
JOB DUTIES & RESPONSIBILITIES:

  • Conducts audits using client data to identify errors and recover revenue
  • Finds, supports, and documents audit and claims operation.
  • Produces claims
  • Updates claims management system
  • Bills claims to client
  • Reviews contracts, agreements, paperwork, and electronic documents
  • Inspects and evaluates client financial information
  • Provides vendors with claim back-up information
  • Packages claims for vendor and/or client
  • Conducts buyer, contract and document pulls as required
  • Provides support for audit team.
  • Actively contacts vendors as part of the claim production process
  • Independently produces written correspondences to vendor inquiries.
  • Analyses and assesses problems regarding client’s claims procedure and business operations based on appropriate audit concepts.
  • Produces number and dollar volume of claims goals as defined by team leader and/or management.
  • Adheres to the overall timing and deadline of an audit cycle.
    REQUIRED WORK EXPERIENCE:
    Extensive PC skills including knowledge of Microsoft Office and preferably database experience
    FUNCTIONAL COMPETENCIES:
    Domain/Industry Knowledge & Focus
  • Understands the core concepts and tasks of recovery audit
  • Familiar with assigned customer base
  • Basic understanding of commercial recovery productivity
  • Little to no understanding of broader industry
  • Able to effectively review one project or vendor complexity level after training period
    WORKING CONDITIONS:
    Benefits include: Medical and Dental Schemes, Pension Scheme, Life Cover, Income Protection, 25 days holiday plus Bank Holidays, On-Line Learning Portal, Employee Assistance Programme, Subsidised Gym Membership, Eye Care, Cycle to Work Scheme, Enhanced Maternity and Paternity Pay

Related Jobs

View all jobs

Marketing and Business Development Coordinator

Functional Data Lead - French Speaking

Associate Director, Strategic Intelligence, Africa

MECHANICAL PRODUCTION ENGINEER - CAD/PDM SPECIALIST

Senior Accountant (m/f/d) UK and France

Strategic Partner Manager, Telco Ecosystem Partnerships London, UK • Business Development & Par[...] (Basé à London)

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.

Data Science Jobs for Non‑Technical Professionals: Where Do You Fit In?

Beyond Jupyter Notebooks Ask most people what a data‑science career looks like and they’ll picture Python wizards optimising XGBoost hyper‑parameters. The truth? Britain’s data‑driven firms need storytellers, strategists, ethicists and project leaders every bit as much as they need statisticians. The Open Data Institute’s UK Data Skills Gap 2024 places demand for non‑technical data talent at 42 % of all data‑science vacancies—roles focused on turning model outputs into business value and trustworthy decisions. This guide highlights the fastest‑growing non‑coding roles, the transferable skills many professionals already have, and a 90‑day action plan to land a data‑science job—no pandas required.

McKinsey & Company Data‑Science Jobs in 2025: Your Complete UK Guide to Turning Data into Impact

When CEOs need to unlock billion‑pound efficiencies or launch AI‑first products, they often call McKinsey & Company. What many graduates don’t realise is that behind every famous strategy deck sits a global network of data scientists, engineers and AI practitioners—unified under QuantumBlack, AI by McKinsey. From optimising Formula One pit stops to reducing NHS wait times, McKinsey’s analytics teams turn messy data into operational gold. With the launch of the McKinsey AI Studio in late 2024 and sustained demand for GenAI strategy, the firm is growing its UK analytics headcount faster than ever. The McKinsey careers portal lists 350+ open analytics roles worldwide, over 120 in the UK, spanning data science, machine‑learning engineering, data engineering, product management and AI consulting. Whether you love Python notebooks, Airflow DAGs, or white‑boarding an LLM governance roadmap for a FTSE 100 board, this guide details how to land a McKinsey data‑science job in 2025.

Data Science vs. Data Mining vs. Business Intelligence Jobs: Which Path Should You Choose?

Data Science has evolved into one of the most popular and transformative professions of the 21st century. Yet as the demand for data-related roles expands, other fields—such as Data Mining and Business Intelligence (BI)—are also thriving. With so many data-centric career options available, it can be challenging to determine where your skills and interests best align. If you’re browsing Data Science jobs on www.datascience-jobs.co.uk, you’ve no doubt seen numerous listings that mention machine learning, analytics, or business intelligence. But how does Data Science really differ from Data Mining or Business Intelligence? And which path should you follow? This article demystifies these three interrelated yet distinct fields. We’ll define the core aims of Data Science, Data Mining, and Business Intelligence, highlight where their responsibilities overlap, explore salary ranges, and provide real-world examples of each role in action. By the end, you’ll have a clearer sense of which profession could be your ideal fit—and how to position yourself for success in this ever-evolving data landscape.