A prestigious international city-based law firm close to Chancery Lane is looking to hire a Pricing Analyst to support the firm's commercial reporting evolution.
Salary £50,000 - £60,000Hybrid Working - 3 days office / 2 remotelyChancery Lane This Pricing Analyst position has become available due to an internal promotion and increased workloads and will assist with providing competitive, efficient pricing, financial and analytical support across the firm.
This will involve reporting into the Pricing Manager and having regular interaction with the Revenue and administrative teams to work on varied projects that include design and develop metrics, reporting and analysis to drive key business decisions.
Pricing Analyst Responsibilities include: • Support with pricing and fee arrangement queries for RFP responses• Produce proposed fee arrangements, creating and reviewing pricing reports• Possess a thorough understanding of rates process through Elite 3E• Develop a good understanding of the firm's pricing tools and provide training across the firm on pricing tools • Collaborate with the Pricing Manager the annual rate setting process and annual rates review• Educate Partners and fee earners in the use of pricing tools and assist in the development of matter budgets.• Maintain phase templates and handle any requests that may arise to amend them• Assist with analysis on client rates, fee structures and discounts, advising Partners on how to improve profitability• Comply with Solicitors Regulation Authority (SRA) Standards and other policies Pricing Analyst Requirements include: • Experience in a Pricing/Finance team within a law firm• Working knowledge of Aderant or Elite• An understanding of pricing and calculating fee arrangements• Advanced proficiency in MS Office: Excel - including pivot tables/formulas, PowerPoint, Access, Power BI (not essential)• Proactive, self-learner who is motivated and results-oriented with a positive, team-player attitude• Highly organised, detail-oriented, and able to handle multiple tasks and heavy workloads efficiently