Data Analyst - Monitoring, Evaluation, and Learning (MEL)

Leather Working Group
Newcastle upon Tyne
1 month ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

About Leather Working Group 

Leather Working Group (LWG) is a global not for profit multi-stakeholder initiative that supports and encourages the use of responsibly made leather as a sustainable material by inspiring, educating, and challenging those that produce and use leather. Through collaboration, convening, and standard setting, we are collectively creating a transparent leather value chain that achieves positive impacts aligned to the Sustainable Development Goals. 

 

The Role 

We are looking for a talented and driven Data Analyst to join our Sustainability Team and play a pivotal role in supporting our Monitoring, Evaluation, and Learning (MEL) activities. In this position, you will focus on analyzing data from LWG audits, creating visually impactful dashboards, and generating actionable insights that drive continuous improvements in our certification scheme. You will collaborate closely with both internal teams and external stakeholders to ensure efficient data collection, analysis, and sharing, ultimately contributing to the ongoing success and evolution of the LWG Responsible Leather sustainability system. 


Main responsibilities 

  • Lead and manage MEL activities to assess the performance and sustainability outcomes of the LWG Responsible Leather sustainability system, using findings to support continuous improvement. 
  • Manage projects related to data collection and sharing. 
  • Analyze data from LWG audits and generate visually engaging reports and dashboards.  
  • Present trends, key insights, and areas for improvement, highlighting the effectiveness of the certification scheme over time. 
  • Engage with external stakeholders to understand their data needs, identify gaps, and feed back new requirements internally. 
  • Develop and implement guidance to ensure high-quality data collection processes. 
  • Work with internal teams to manage data access permissions and implement security measures to protect sensitive information. 


Qualifications 

  • Strong data analysis skills, with experience in using data visualization tools such as Power BI. 
  • Strong understanding of Monitoring, Evaluation, and Learning (MEL) frameworks and their application in sustainability certification schemes. 
  • Project management skills 
  • Ability to collaborate effectively with internal and external stakeholders. 
  • Strong communication skills, both written and verbal, with the ability to present complex data findings clearly to diverse audiences. 
  • A background in sustainability or knowledge of the ISEAL Code of Good Practice for sustainability systems would be an advantage. 
  • Ability to manage time in an environment with competing demands. 
  • Pro-active and willing to make suggestions for improvements.  
  • Willingness to learn and adapt in a growing organization. 

 

Application process

  • Complete the LinkedIn application. 
  • Short-listed candidates will be contacted for a cover letter 

Due to the high number of applications we receive, we regret that applicants who are not short listed will not be contacted.


Employment Package 

Reports to: Director of Sustainability 

Position: Full-Time Position, 37.5 Hours a Week   

Location: Remote, UK-based 

Salary Range: £55-60,000 


Our Values 

At Leather Working Group, we are committed to fostering a responsible, open, and respectful environment where each team member can thrive and contribute to meaningful progress. Our values guide our actions, our interactions, and our shared goals as we work together to make a positive impact. 


As an organisation, we believe in the power of collaboration and cross-functional teamwork, supporting LWG’s values in all that we do. We share knowledge generously, engage in constructive debate, and build a workplace rooted in mutual respect and trust.  

We value a friendly, cheerful, and enthusiastic team where it is safe to challenge ideas, admit mistakes, and celebrate successes together. Diversity of thought and alignment in purpose help us move forward effectively, making our workplace a positive and supportive environment for all. 


Leather Working Group is committed to promoting equal opportunities in employment and creating a workplace culture in which diversity and inclusion is valued and everyone is treated with dignity and respect. As part of our zero-tolerance approach to discrimination in any form, any job applicants will receive equal treatment regardless of age, disability, gender reassignment, marital or civil partner status, pregnancy or maternity, race, colour, nationality, ethnic or national origin, religion or belief, sex or sexual orientation (Protected Characteristics). 

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.

Top 10 Mistakes Candidates Make When Applying for Machine-Learning Jobs—And How to Avoid Them

Landing a machine-learning job in the UK is competitive. Learn the 10 biggest mistakes applicants make—plus tested fixes, expert resources and live links that will help you secure your next ML role. Introduction From fintechs in London’s Square Mile to advanced-research hubs in Cambridge, demand for machine-learning talent is exploding. Job boards such as MachineLearningJobs.co.uk list new vacancies daily, and LinkedIn shows more than 10,000 open ML roles across the UK right now. Yet hiring managers still reject most CVs long before interview—often for avoidable errors. Below are the ten most common mistakes we see, each paired with a practical fix and a live resource link so you can dive deeper.

Top 10 Best UK Universities for Machine Learning Degrees (2025 Guide)

Explore ten UK universities that deliver world-class machine-learning degrees in 2025. Compare entry requirements, course content, research strength and industry links to find the programme that fits your goals. Machine learning (ML) has shifted from academic curiosity to the engine powering everything from personalised medicine to autonomous vehicles. UK universities have long been pioneers in the field, and their programmes now blend rigorous theory with hands-on practice on industrial-scale datasets. Below, we highlight ten institutions whose undergraduate or postgraduate pathways focus squarely on machine learning. League tables move each year, but these universities consistently excel in teaching, research and collaboration with industry.

How to Write a Winning Cover Letter for Machine Learning Jobs: Proven 4-Paragraph Structure

Learn how to craft the perfect cover letter for machine learning jobs with this proven 4-paragraph structure. Ideal for entry-level candidates, career switchers, and professionals looking to advance in the machine learning sector. When applying for a machine learning job, your cover letter is a vital part of your application. Machine learning is an exciting and rapidly evolving field, and your cover letter offers the chance to demonstrate your technical expertise, passion for AI, and your ability to apply machine learning techniques to solve real-world problems. Writing a cover letter for machine learning roles may feel intimidating, but by following a clear structure, you can showcase your strengths effectively. Whether you're just entering the field, transitioning from another role, or looking to advance your career in machine learning, this article will guide you through a proven four-paragraph structure. We’ll provide practical tips and sample lines to help you create a compelling cover letter that catches the attention of hiring managers in the machine learning job market.