Finance Data Analyst - Hybrid: Build Cost Models & Reports in Leeds

Finance Data Analyst - Hybrid: Build Cost Models & Reports in Leeds

Leeds Full-Time 31500 - 38500 Β£ / year (est.) Home office (partial)
Polaris Consulting International

At a Glance

  • Tasks: Create cost models and reports to support strategic financial decisions.
  • Company: Gibson Hollyhomes, a dynamic firm in Leeds City Centre.
  • Benefits: Flexible hybrid working arrangements and a vibrant work environment.
  • Other info: Great opportunity for career growth in a supportive atmosphere.
  • Why this job: Join a forward-thinking team and make an impact in finance analytics.
  • Qualifications: STEM degree in Mathematics, Economics or Science; data proficiency required.

The predicted salary is between 31500 - 38500 Β£ per year.

Gibson Hollyhomes Leeds is seeking a Finance Data Analyst for an international client based in Leeds City Centre.

The role focuses on delivering timely reporting and building cost-analysis models to support strategic decisions.

Ideal candidate is a STEM graduate with a degree in Mathematics, Economics or Science, proficient with data and financial metrics.

Hybrid working in Leeds city centre provides flexible arrangements.

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Finance Data Analyst - Hybrid: Build Cost Models & Reports in Leeds employer: Polaris Consulting International

Emerald Group Ltd is an exceptional employer that fosters a dynamic and rewarding work culture in Plymouth, where your achievements directly impact your earnings and career growth. With a strong emphasis on recognising hard work and high performance, we provide our Sales Executives with the tools and support needed to thrive in their roles while enjoying a fulfilling journey towards success.

Polaris Consulting International

Contact Details:

Polaris Consulting International Recruitment Team

We think you need these skills to ace Finance Data Analyst - Hybrid: Build Cost Models & Reports in Leeds

Communication Skills
Automation
SQL
Problem-Solving Skills
Python
Attention to Detail
Data Engineering