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Reward, Remote (Remote)
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Page 3 of 6
Remote (Remote) 2671.46 miles
£45000.00-£55000.00 per year
Permanent
Job description

Team: Reward & Talent Acquisition

Location: Homebased

Work pattern: 35 hours per week, Monday to Friday

Salary: Up to £51,869.00 per annum

Contract: Permanent

We are the UK’s largest cat welfare charity. All over the country, our passionate employees, volunteers and supporters are using their kindness and expertise to make life better for millions of cats and the people who care for them.

Will you join us and make life better for cats?

Responsibilities of our Reward Specialist:

  • providing reward advice and guidance, including pay, job evaluation and reward and recognition approaches
  • to influence, challenge and be credible with stakeholders at all seniority levels, including CEO and Trustees
  • supporting in developing reward strategies, including pay frameworks and wellbeing initiatives
  • ensuring the reward strategy remains current, affordable and reflects the needs and culture of Cats Protection
  • responsible for the accurate and considered cost modelling of the annual pay review process
  • develop and maintain the Reward ‘roadmap’ and reward activity plan
  • lead on job evaluation, using the Hay Methodology
  • responsible for all aspects of salary benchmarking
  • responsible for the gender pay gap analysis, preparation and delivery

About the Reward & Talent Acquisition team:

  • we sit within the People & Culture directorate
  • responsible for developing reward strategies, including pay frameworks and wellbeing initiatives, the development and improvement of inspiring benefits, cost effective offering, working within regulatory, safeguarding and compliance frameworks and driving Cat Protection’s employer brand
  • we currently have a team of six working across reward and recruitment, consisting of Head of Reward & Talent Acquisition, Talent Acquisition Manager, three Talent Acquisition Partners and a Reward & Recruitment Officer. We have vacancies for a Reward Specialist and Reward & Benefits Officer
  • this role will line manage the Reward & Benefits Officer

What we’re looking for in our Reward Specialist:

  • significant reward experience including the implementation of pay policy and frameworks
  • a strategic thinker who rolls-up their sleeves and gets stuck in with the basics
  • experience of job evaluation using Hay
  • excellent planning and organisational skills with proven ability to multi-task and work on own initiative,
  • experience of implementing pay reviews (and being a whizz with Excel)
  • someone who gets excited about employer branding and the impact reward has on attracting talent
  • a positive ‘can-do’ approach, and a creative mentality to achieve the best results
  • a passion for developing a high performing team and supporting the personal development of direct report
  • CIPD qualification or equivalent Reward experience

What we can offer you:

  • range of health benefits
  • 26 days’ annual leave plus bank holidays, increasing with length of service
  • Salary Finance, which empowers you to take control of your financial wellbeing
  • and much more, which you can learn about 

Interested? Here’s how to apply:

Application closing date: 01 December 2025

Virtual interview date: 16 December 2025

Applications may close before the deadline, so please apply early to avoid disappointment. Please note, applications received after the closing date may not be responded to.

If successful, your recruitment journey will include:

Application

  1. Anonymised application form
  2. Video screening

Interview

  1. Virtual interview via Microsoft Teams along with a presentation

Please note, the process may change slightly dependent on application numbers. We will inform you of any relevant changes.

Please email [email protected] if you require any adjustments to be made for you to complete your application or to participate in the recruitment journey

Posted on: 18 November 2025
Closing date: 01 December 2025 at 23:59
Job ref: PC 11
Tags: Human Resources, Data Analysis