Circular Economy Specialist

Role Purpose & Context

Role Summary

The Circular Economy Specialist is responsible for owning specific data streams and reporting processes related to our environmental impact and circularity goals. This means you'll be gathering, analysing, and reporting on things like waste volumes, recycled content, and material flows across a particular region or product category. You'll sit squarely within our Compliance, Quality, Health, and Safety team, working closely with colleagues in Operations, Procurement, and Product Development. When you do this well, we get accurate data that helps us make better decisions, avoid fines, and genuinely improve our environmental performance. If it's not done properly, we risk regulatory penalties, reputational damage, and, frankly, we just won't know if we're actually making a difference. The tricky part is often getting consistent, reliable data from disparate sources. The reward, though, is seeing your careful work directly inform our sustainability reports and influence real-world changes in how we design, make, and manage our products.

Reporting Structure

• Reports to: Senior Circular Economy Specialist or Lead Circular Economy Strategist
• Direct reports: None, though you'll often guide new joiners informally.
• Matrix relationships: Sustainability Data Analyst, Environmental Compliance Officer, EPR Coordinator,

Key Stakeholders

Internal:

• Regional Operations Managers (for waste and material data)
• Procurement Analysts (for supplier data and recycled content)
• Product Development Engineers (for design for circularity inputs)
• EHS Site Leads (for local compliance data)
• Marketing & Communications (for data to support external claims)

External:

• External auditors (for data validation)
• EPR compliance schemes (for reporting accuracy)
• Waste management partners (for data reconciliation)

Organisational Impact

Scope: Your work directly underpins our ability to meet regulatory obligations, report accurately on our sustainability performance, and identify opportunities for material efficiency and waste reduction. Frankly, without solid data, our circular economy strategy is just talk. You'll provide the evidence that proves we're making progress.

Performance Metrics

Quantitative Metrics

1. Metric: Data Accuracy for Key Circularity Metrics
2. Desc: The precision and correctness of waste, water, and material data entered into our EHS and reporting systems.
3. Target: Greater than 98% accuracy on all audited data points.
4. Freq: Quarterly audits and spot checks.
5. Example: If we audit 100 data entries for plastic waste at a site, no more than two should have discrepancies or errors. You'll catch the £5,000 miscalculation before it hits the report.
6. Metric: Reporting Timeliness
7. Desc: Ensuring all routine compliance and internal data reports are submitted by their agreed deadlines.
8. Target: 100% of routine reports delivered on time.
9. Freq: Monthly tracking against internal reporting calendar.
10. Example: Your monthly EPR data submission for the German market is due on the 15th; it's consistently submitted on or before that date, every single month. No last-minute scrambles.
11. Metric: Task Completion Rate
12. Desc: The volume of data analysis and reporting tasks completed within agreed timeframes.
13. Target: Successfully complete 15-20 data analysis and reporting tasks per month.
14. Freq: Weekly review of project management tool and task list.
15. Example: You'll typically close out all assigned data validation tickets and complete your allocated sections of the quarterly sustainability report within the expected sprint cycles.
16. Metric: Material Flow Analysis (MFA) Coverage
17. Desc: The scope and depth of material flow data collected and analysed for assigned product lines or regions.
18. Target: Successfully map material flows for 2-3 new product lines or 1 new region annually, identifying key circularity hotspots.
19. Freq: Annual project review.
20. Example: You'll complete the MFA for our new 'Eco-Line' product, identifying that 70% of its total material mass is currently linear, giving us clear targets for improvement.

Qualitative Metrics

1. Metric: Proactive Issue Identification
2. Desc: How well you spot potential data quality problems, compliance risks, or opportunities for improvement before they become bigger issues.
3. Evidence: You're the one flagging a discrepancy in waste data from a new site, or pointing out that a new product design might fall foul of an upcoming plastics tax. You'll bring solutions, not just problems, to your manager.
4. Metric: Clarity of Communication
5. Desc: Your ability to explain complex circularity data and compliance requirements in a way that non-experts (like operations managers or marketing teams) can easily understand and act upon.
6. Evidence: Stakeholders consistently say your reports are easy to read and your explanations are clear. You can distil a dense regulatory update into a few actionable bullet points for a regional team. You won't use jargon unless absolutely necessary, and then you'll explain it.
7. Metric: Process Adherence & Improvement
8. Desc: Your commitment to following established data collection and reporting processes, and your willingness to suggest practical improvements.
9. Evidence: You consistently follow our data validation protocols. You'll also suggest, for example, a small tweak to a data entry form that could save 10 minutes per week for 5 people, making a real difference over time.
10. Metric: Collaboration with Internal Teams
11. Desc: Your effectiveness in working with other departments to gather data, clarify requirements, and support their circularity efforts.
12. Evidence: You'll get a 'thank you' email from a Procurement colleague for helping them understand a new recycled content standard, or an Operations manager will proactively share data because they trust your requests. You're seen as helpful, not just 'the data person'.

Primary Traits

• Trait: Data Detective
• Manifestation: You're the person who notices the waste report from Site B is consistently 10% lower than similar sites, and you don't just accept it. You'll dig into the raw data, question the collection methods, and figure out if it's a genuine improvement or a reporting error. You'll spot that a material's weight has been entered in grams instead of kilograms, catching a massive error before it skews our overall footprint.
• Benefit: Our circular economy claims and compliance depend entirely on accurate data. One misplaced decimal point or unverified assumption can lead to greenwashing accusations, regulatory fines, or simply making terrible business decisions. We need someone who instinctively questions the numbers, not just takes them at face value.
• Trait: Process Owner
• Manifestation: When you're given a task, you own it from start to finish. You don't just do the work; you think about the steps, the dependencies, and the quality. If you're responsible for the quarterly EPR report, you'll make sure all the inputs are gathered on time, the calculations are correct, and it's submitted precisely when it needs to be. You're not waiting to be chased.
• Benefit: Many of our circularity programmes involve complex, recurring data collection and reporting. If these processes aren't reliably executed, we miss deadlines, incur penalties, and lose credibility. We need someone who takes pride in delivering consistent, high-quality outputs without constant supervision.
• Trait: Practical Problem Solver
• Manifestation: You don't just identify a problem ('the data from Site C is always incomplete'); you think about how to fix it ('I'll build a simpler spreadsheet template for them, or suggest a quick training session'). You're not afraid to roll up your sleeves and find a workable, even if not perfect, solution to keep things moving. You'll propose a workaround for a missing data point rather than just saying 'I can't do this'.
• Benefit: The reality of circular economy work is often messy data, imperfect systems, and constantly evolving requirements. We need people who can navigate these challenges with a pragmatic mindset, finding solutions that move us forward rather than getting stuck waiting for ideal conditions. Perfection is the enemy of progress here.

Supporting Traits

• Trait: Organised
• Desc: You'll manage multiple data streams and reporting deadlines. Keeping track of what's due when, and where all the necessary inputs are, is absolutely crucial. Think clear folder structures and meticulously updated task lists.
• Trait: Inquisitive
• Desc: You'll have a natural curiosity about 'how things work' and 'why things are the way they are'. This helps you understand the underlying processes that generate the data you're working with, which is key to spotting issues and suggesting improvements.
• Trait: Collaborative
• Desc: You'll spend a fair bit of time working with people from different teams – Operations, Procurement, Product. Being able to work well with others, even when asking for data that might feel like 'extra work' to them, is really important.

Primary Motivators

1. Motivator: Making a Tangible Environmental Impact
2. Daily: You'll get a real kick out of seeing the waste reduction figures improve, or the recycled content percentage go up, knowing that your meticulous data work directly contributed to those changes. It's about seeing the numbers reflect real-world positive change.
3. Motivator: Solving Complex Data Puzzles
4. Daily: If you enjoy the challenge of taking messy, incomplete data and turning it into clear, actionable insights, you'll love this. It's like being a detective, piecing together clues to form a complete picture.
5. Motivator: Ensuring Compliance and Avoiding Risk
6. Daily: There's a quiet satisfaction in knowing that your work keeps the company out of trouble, preventing fines and reputational damage. You'll appreciate the structure and importance of regulatory adherence.

Potential Demotivators

Honestly, this role involves a fair bit of repetitive data entry and validation. You'll spend a lot of time chasing people for data, and sometimes you'll get incomplete or inconsistent information. You might build a brilliant dashboard only for it to be used once, or develop a new reporting process that gets changed again six months later due to a new regulation. If you need constant, highly visible strategic wins, or if you get frustrated by the grind of data management and stakeholder nudging, this might not be the right fit.

Common Frustrations

1. Chasing colleagues for overdue data submissions, sometimes multiple times.
2. Dealing with inconsistent data formats from different sites or suppliers.
3. Spending time on reports that don't seem to get much attention from leadership.
4. The slow pace of change when trying to implement new data collection processes.
5. Having to explain basic circular economy concepts repeatedly to new stakeholders.

What Role Doesn't Offer

1. A clear path to immediate people management (that comes later).
2. A role where you're solely focused on high-level strategy without getting into the details.
3. A 'set it and forget it' environment; things are always evolving.
4. A role where every single piece of your work leads to a major, celebrated business transformation.

ADHD Positives

1. The varied nature of data sources and reporting requirements could keep things interesting, preventing boredom.
2. The 'detective' aspect of spotting data anomalies might tap into hyperfocus strengths.
3. Clear, structured reporting deadlines can provide external motivation and structure.

ADHD Challenges and Accommodations

1. Repetitive data entry or chasing can be challenging; we can explore automation tools to minimise this.
2. Prioritising multiple data requests might be tricky; clear task management systems and regular check-ins with your manager will be key.
3. Attention to detail for long reports can be tiring; using checklists and peer review can help catch errors.

Dyslexia Positives

1. Strong visual thinking can be a huge asset in understanding complex data flows and identifying patterns that others might miss.
2. The problem-solving aspect, particularly in finding creative solutions to data inconsistencies, could be a strong suit.

Dyslexia Challenges and Accommodations

1. Extensive reading of regulatory documents or detailed reports might be time-consuming; we can provide text-to-speech software or allow more time for review.
2. Drafting detailed narratives for reports could be challenging; we encourage the use of templates, bullet points, and AI-assisted writing tools (more on this below).
3. Proofreading your own work for typos is crucial; using grammar checkers and peer review is standard practice here.

Autism Positives

1. A strong preference for logical systems and data accuracy aligns perfectly with the core of this role.
2. The ability to focus deeply on specific tasks, like data validation or building detailed reports, can be a significant strength.
3. Clear processes and defined reporting structures can provide a comfortable and predictable work environment.

Autism Challenges and Accommodations

1. Navigating informal social dynamics when chasing data from different teams might be challenging; we can support with clear communication templates and guidance on preferred contact methods.
2. Unexpected changes in data requirements or project scope could be unsettling; we'll aim for clear communication about changes and provide support to adapt.
3. Sensory overload from open-plan offices can be an issue; we offer noise-cancelling headphones and quiet zones.

Key Responsibilities

Experience Levels Responsibilities

1. Level: Mid-Level Professional (2-5 years experience)
2. Responsibilities: Manage and maintain data streams for specific circularity metrics (e.g., waste generation, recycled content, water usage) for an assigned region or product category. This means you'll be the go-to person for those numbers, ensuring they're accurate and up-to-date.
3. Draft routine compliance reports for various Extended Producer Responsibility (EPR) schemes, gathering the necessary data and ensuring it meets regulatory requirements. You'll be checking the boxes, making sure we're not missing anything.
4. Support Life Cycle Assessment (LCA) studies by gathering relevant input data (e.g., material quantities, energy consumption) and extracting results from pre-built models for reporting purposes. You won't be building LCAs from scratch yet, but you'll be feeding them.
5. Identify inconsistencies or gaps in circularity data and propose practical solutions to improve data quality and collection processes. You're not just reporting the problem; you're thinking about how to fix it.
6. Develop and maintain simple dashboards and visualisations using our BI tools to track progress against circularity targets for your assigned areas. This helps us see at a glance if we're on track.
7. Collaborate with internal teams like Procurement and Operations to understand their data needs and provide them with accurate information to support their circularity initiatives. You'll be a helpful resource for them.
8. Stay updated on relevant environmental regulations and reporting standards (like GRI or CSRD) that impact your areas of responsibility, flagging any changes to your manager. You'll be our eyes and ears on the ground for regulatory shifts.
9. Supervision: You'll have weekly check-ins with your manager to discuss progress, troubleshoot issues, and align on priorities. For routine tasks, you'll work independently, but for anything novel or complex, you'll be expected to consult and get guidance.
10. Decision: You can make routine decisions within established guidelines, for example, choosing the best way to clean a specific dataset or how to present data in a standard report. Any decisions that impact other teams, require budget, or involve significant changes to processes will need to be escalated to your manager for approval.
11. Success: Success looks like consistently delivering accurate, timely reports, proactively identifying and addressing data quality issues, and being a reliable, trusted resource for circularity data within your scope. Your dashboards are clear, and your data is clean.

Decision-Making Authority

• Type: Data Collection Methodology
• Entry: Follows established procedures; escalates any deviations.
• Mid: Chooses appropriate methods for routine data collection; proposes improvements to manager.
• Senior: Designs new data collection methodologies; approves changes to existing processes for their workstream.
• Type: Reporting Content & Format
• Entry: Populates templates with data; seeks review for all content.
• Mid: Drafts full reports based on guidelines; proposes minor formatting/content adjustments.
• Senior: Defines report content and structure for their workstream; makes recommendations for executive reporting.
• Type: Issue Resolution (Data Quality)
• Entry: Identifies data issues; escalates to supervisor for resolution.
• Mid: Investigates root cause of data issues; proposes and implements solutions for routine problems.
• Senior: Resolves complex, cross-functional data quality issues; designs preventative measures.
• Type: Stakeholder Communication
• Entry: Responds to direct requests with guidance; informs supervisor of all external contact.
• Mid: Communicates directly with internal peers and clients on data requests; informs manager of significant interactions.
• Senior: Leads communication with key internal and external stakeholders on project status and findings; consults director on sensitive topics.

Competency Requirements

Foundation Skills (Transferable)

These are the bedrock skills that let you do your job well, no matter the specific task. They're about how you think, communicate, and organise your work.

• Category: Communication & Collaboration
• Skills: Clear Written Communication: You'll need to write clear, concise reports and emails that explain complex data without jargon. Think about getting your point across effectively to someone who isn't an expert.
• Active Listening: When someone explains their data collection process, you'll really listen to understand their challenges and context, not just wait for your turn to speak. This helps you get better data.
• Cross-functional Collaboration: You'll work with people from different departments (Operations, Procurement, Product). Being able to build rapport and work together, even when there are conflicting priorities, is key.
• Category: Problem-Solving & Analysis
• Skills: Analytical Thinking: You'll take raw data, break it down, spot patterns, and draw logical conclusions. It's about seeing beyond the numbers to understand what they actually mean for the business.
• Root Cause Analysis: When you find a data discrepancy, you won't just note it; you'll dig into why it happened. Was it a process error? A system glitch? A misunderstanding?
• Structured Problem Solving: You'll approach problems in a logical, step-by-step way, even when the data is messy or the requirements are vague. You'll know how to start, even if you don't know the full answer.
• Category: Organisation & Execution
• Skills: Time Management: You'll be juggling multiple data requests and reporting deadlines. Being able to prioritise your workload and meet commitments is non-negotiable.
• Attention to Detail: This is absolutely critical. One wrong number in a compliance report can have serious consequences. You'll have a keen eye for accuracy and consistency.
• Process Adherence: We have established ways of doing things, especially for data collection and reporting. You'll need to follow these processes diligently, and suggest improvements where you see them.
• Category: Adaptability & Initiative
• Skills: Adaptability to Change: Regulations change, data sources evolve, and business priorities shift. You'll need to be comfortable adjusting your plans and learning new approaches.
• Proactive Learning: If there's a new regulation or a new feature in a software tool, you won't wait to be told. You'll go out and learn about it yourself, bringing that knowledge back to the team.
• Taking Initiative: When you spot an opportunity to improve a process or fix a data issue, you'll take the lead in addressing it, rather than waiting for someone else to assign it.

Functional Skills (Role-Specific Technical)

These are the specific methodologies, technical tools, and industry knowledge you'll need to apply day-to-day in this role.

Technical Competencies

• Skill: Life Cycle Assessment (LCA) Methodology (ISO 14040/14044)
• Desc: Understanding the basics of LCA, including how to define the scope of a study, identify impact categories, and interpret results from existing LCA models. You'll know what 'cradle-to-gate' means and why it matters.
• Level: Intermediate
• Skill: Extended Producer Responsibility (EPR) Policy Analysis
• Desc: Practical knowledge of how EPR schemes work, especially for packaging, WEEE, or batteries, in key regions like the EU or UK. You'll understand the data requirements and reporting obligations for these schemes.
• Level: Intermediate
• Skill: Material Flow Analysis (MFA)
• Desc: The ability to track material inputs, outputs, and waste streams for a product or facility. You'll be able to identify where materials are going and where the biggest losses or opportunities for circularity lie.
• Level: Basic
• Skill: Sustainability Reporting Standards (GRI, SASB, CSRD)
• Desc: Familiarity with the structure and key reporting requirements of common sustainability frameworks. You'll understand what data points are needed for each and why they're important for different audiences.
• Level: Intermediate
• Skill: Data Validation & Quality Assurance
• Desc: The ability to check data for accuracy, completeness, and consistency, identifying errors and implementing basic quality control measures. You'll know how to spot a dodgy number.
• Level: Intermediate

Digital Tools

• Tool: LCA Software (e.g., SimaPro, GaBi)
• Level: Intermediate
• Usage: Running pre-built LCA models, extracting specific impact data for reports, and understanding the basic interface.
• Tool: Material Traceability Platforms (e.g., Circulor, Sourcemap)
• Level: Basic
• Usage: Entering and validating supplier data, tracking specific material shipments, and pulling standard reports on material provenance.
• Tool: EHS/Compliance Software (e.g., Enablon, Sphera)
• Level: Intermediate
• Usage: Entering waste and resource consumption data, generating monthly compliance reports, and tracking non-conformance issues related to environmental performance.
• Tool: GRC System (e.g., ServiceNow GRC, OneTrust)
• Level: Basic
• Usage: Responding to data requests related to circular economy risks, tracking the completion of assigned risk mitigation tasks within the system.
• Tool: BI & Data Visualisation (e.g., Power BI, Tableau)
• Level: Intermediate
• Usage: Using pre-built dashboards to answer specific business questions, exporting data for further analysis, and building simple charts to illustrate trends in circularity metrics.
• Tool: Microsoft Excel (Advanced)
• Level: Advanced
• Usage: Cleaning and manipulating large datasets, building complex formulas (VLOOKUP, INDEX/MATCH, SUMIFS), and creating pivot tables for ad-hoc analysis. Honestly, you'll live in Excel.

Industry Knowledge

• Area: Circular Business Model Concepts
• Desc: A foundational understanding of different circular strategies like Product-as-a-Service, remanufacturing, and reverse logistics. You'll know the theory, even if you're not designing them yet.
• Area: Waste Management Principles
• Desc: Understanding the waste hierarchy (reduce, reuse, recycle) and common waste streams in a manufacturing or retail context. You'll know the difference between pre-consumer and post-consumer waste.
• Area: Sustainable Materials Science (Basic)
• Desc: Familiarity with common sustainable materials (e.g., recycled plastics, bio-based materials) and their basic properties, as well as an understanding of material certifications.

Regulatory Compliance Regulations

• Reg: Extended Producer Responsibility (EPR) Regulations (EU/UK focus)
• Usage: Understanding the specific data requirements for packaging, WEEE, or battery EPR schemes, ensuring accurate reporting and fee calculations for assigned regions.
• Reg: ISO 14001 (Environmental Management Systems)
• Usage: Understanding how our EMS works and how circularity data feeds into our environmental objectives and targets. You'll know your role in maintaining compliance.
• Reg: Corporate Sustainability Reporting Directive (CSRD) (EU)
• Usage: Familiarity with the key reporting pillars and data points required under CSRD, particularly those related to resource use, waste, and circularity. You'll know how your data contributes.

Essential Prerequisites

• Proven experience (2-5 years) in environmental data management, sustainability reporting, or compliance roles.
• A solid grasp of data analysis principles and experience with large datasets.
• Demonstrable ability to work independently on routine tasks and manage multiple deadlines.
• Experience with at least one EHS or sustainability reporting software.
• A genuine interest in circular economy principles and their practical application in a business context.

Career Pathway Context

These are the skills you should already have in your toolkit. They're the foundation we'll build upon. If you've been an Environmental Analyst or a Junior Compliance Officer, you'll likely have many of these covered. We're looking for someone who can hit the ground running on data management and reporting, not someone starting from scratch.

Qualifications & Credentials

Emerging Foundation Skills

• Skill: Digital Product Passport (DPP) Data Management
• Why: The EU's Digital Product Passport (DPP) is coming, and it's a game-changer. It means we'll need to collect and manage vast amounts of product-specific data on materials, repairability, and end-of-life options. This isn't just a regulatory hurdle; it's an opportunity to provide transparency and enable circular business models.
• Concepts: [{'concept_name': 'DPP Data Requirements', 'description': 'Understanding what specific data points (e.g., material composition, recycled content, repair instructions) will be mandated for different product categories.'}, {'concept_name': 'Data Interoperability', 'description': 'How to ensure data from our internal systems (ERP, PLM) can be seamlessly integrated and shared with external DPP platforms.'}, {'concept_name': 'Supplier Data Collection for DPPs', 'description': 'Strategies for working with suppliers to gather the granular material and component data needed for DPPs.'}, {'concept_name': 'Blockchain for Traceability (Basic)', 'description': 'A basic understanding of how blockchain technology might be used to secure and verify DPP data.'}]
• Prepare: This month: Read the latest EU proposals on DPPs for our industry sector. Understand the scope and timeline.
• Next quarter: Map out what data points we currently collect that could contribute to a DPP, and identify key gaps.
• Month 3-6: Work with your manager to identify a pilot product for a 'mock' DPP data collection exercise.
• Month 6-12: Attend webinars or industry workshops on DPP implementation best practices.
• QuickWin: Start familiarising yourself with the concept of a 'material passport' and how it differs from a traditional bill of materials. Talk to Product Development about what data they already hold on components.
• Skill: Advanced Data Validation & Automation Techniques
• Why: As data volumes grow and reporting requirements become more complex, manual data validation simply won't cut it. We need to move towards more automated, robust systems to ensure accuracy and free up your time for higher-value analysis. This isn't just about efficiency; it's about reducing human error.
• Concepts: [{'concept_name': 'Automated Data Quality Checks', 'description': 'Setting up rules and scripts (e.g., in Excel or Python) to automatically flag common data errors (outliers, missing values, incorrect formats).'}, {'concept_name': 'Data Reconciliation Strategies', 'description': 'Methods for comparing data from different sources (e.g., waste haulier invoices vs. internal EHS system) to identify and resolve discrepancies efficiently.'}, {'concept_name': 'Basic Scripting for Data Transformation', 'description': 'Learning simple scripting (e.g., Python with pandas) to clean, transform, and standardise messy data more quickly than manual Excel work.'}, {'concept_name': 'API Integration Concepts (Basic)', 'description': "Understanding how different software systems can 'talk' to each other to automate data transfer, reducing manual entry."}]
• Prepare: This week: Identify one recurring data validation task you do manually. Can you build an Excel formula to automate part of it?
• This month: Explore online tutorials for basic Python scripting for data cleaning (e.g., Codecademy, DataCamp).
• Next quarter: Work with a senior colleague to implement one automated data quality check within our EHS system or a shared spreadsheet.
• Month 3-6: Look for opportunities to reconcile two different data sources automatically, identifying discrepancies.
• QuickWin: Start using advanced Excel features like 'Data Validation' and 'Conditional Formatting' to automatically highlight potential errors in your spreadsheets. It's a small step, but it makes a big difference.

Advancing Technical Skills

• Skill: Advanced EHS/Compliance Software Configuration
• Why: As our internal processes and external reporting needs evolve, you'll need to be able to do more than just enter data. You'll start to configure new data collection modules or design custom reports within our EHS software, moving beyond standard functionalities.
• Concepts: [{'concept_name': 'Custom Report Building', 'description': 'Designing and implementing non-standard reports within the EHS system to meet specific internal or external stakeholder needs.'}, {'concept_name': 'Module Configuration', 'description': 'Setting up new data input fields, workflows, or sections within the EHS software to capture new circularity metrics.'}, {'concept_name': 'User Access Management (Basic)', 'description': 'Understanding how to manage permissions and roles within the EHS system for different users.'}]
• Prepare: This month: Ask your manager for access to the EHS system's 'test' or 'development' environment to experiment with report building.
• Next quarter: Shadow a senior colleague who is configuring a new module or designing a complex report.
• Month 3-6: Take responsibility for building one new custom report for a specific internal stakeholder.
• Month 6-12: Complete any vendor-provided training modules on advanced configuration for our EHS software.
• QuickWin: Explore all the existing reports and dashboards within our EHS system. Understand how they're built and what data they pull. This gives you a foundation for customisation.

Education Requirements

• Level: Minimum
• Req: A Bachelor's degree in Environmental Science, Environmental Engineering, Sustainability, Data Science, or a closely related field.
• Alts: We're open to candidates with equivalent practical experience (typically 4+ years in a relevant role) who can demonstrate a strong understanding of environmental data management and compliance principles. Show us what you've done, not just what you've studied.

Experience Requirements

You'll need roughly 2-5 years of hands-on experience in a role focused on environmental compliance, sustainability reporting, or managing environmental data. This isn't an entry-level position; we're looking for someone who's already comfortable with the day-to-day grind of data collection, validation, and basic reporting. Experience working within a manufacturing, retail, or logistics environment would be a definite plus, as that's where much of our data comes from.

Preferred Certifications

• Cert: IEMA Foundation Certificate in Environmental Management
• Prod: Institute of Environmental Management & Assessment (IEMA)
• Usage: Demonstrates a foundational understanding of environmental management principles, which is highly relevant to our compliance and circularity work.
• Cert: Certified Waste Management Professional (CWMP)
• Prod: Various national bodies (e.g., CIWM in the UK)
• Usage: Shows practical knowledge of waste management, which is a core component of circular economy data and reporting.
• Cert: Professional Certificate in Data Analysis (e.g., from Google or IBM)
• Prod: Coursera, edX, etc.
• Usage: Highlights strong data analysis skills, which are essential for this data-heavy role, even if your degree wasn't in data science.

Recommended Activities

• Attending webinars or online courses on new environmental regulations (e.g., upcoming EU directives).
• Participating in industry forums or LinkedIn groups focused on circular economy or sustainability reporting.
• Taking advanced Excel or Power BI courses to deepen your data visualisation skills.
• Reading key reports from organisations like the Ellen MacArthur Foundation to stay abreast of circular economy trends.
• Seeking out opportunities to shadow colleagues in Procurement or Operations to understand their data challenges firsthand.

Career Progression Pathways

Entry Paths to This Role

• Path: Environmental Analyst
• Time: 1-2 years
• Path: Junior Compliance Officer (Environmental Focus)
• Time: 2-3 years
• Path: Sustainability Data Coordinator
• Time: 2-3 years

Career Progression From This Role

• Pathway: Senior Circular Economy Specialist (L3)
• Time: 3-5 years in current role

Long Term Vision Potential Roles

• Title: Lead Circular Economy Strategist (L4)
• Time: 5-8 years from current role
• Title: Circular Economy Manager (L5)
• Time: 8-12 years from current role
• Title: Director of Sustainability & Circularity (L6)
• Time: 12-16 years from current role

How Zavmo Delivers This Role's Development

DISCOVER Phase: Skills Gap Analysis

Zavmo maps your current competencies against all requirements in this job description through conversational assessment. We evaluate your foundation skills (communication, strategic thinking), functional skills (CRM expertise, negotiation), and readiness for career progression.

Output: Personalised skills gap heat map showing strengths and priorities, estimated time to competency, neurodiversity accommodations.

DISCUSS Phase: Personalised Learning Pathway

Based on your DISCOVER results, Zavmo creates a personalised learning plan prioritised by impact: foundation skills first, then functional skills. We adapt to your learning style, pace, and neurodiversity needs (ADHD, dyslexia, autism).

Output: Week-by-week schedule, each module linked to specific job responsibilities, checkpoints and milestones.

DELIVER Phase: Conversational Learning

Learn through conversation, not boring modules. Zavmo uses 10 conversation types (Socratic dialogue, role-play, coaching, case studies) to build competence. Practice difficult QBR presentations, negotiate tough renewals, and handle churn conversations in a safe AI environment before facing real clients.

Example: "For 'Stakeholder Mapping', Zavmo will guide you through analysing a complex enterprise account, identifying key decision-makers, and building an engagement strategy."

DEMONSTRATE Phase: Competency Assessment

Zavmo automatically builds your evidence portfolio as you learn. Every conversation, practice scenario, and application example is captured and mapped to NOS performance criteria. When ready, your portfolio supports OFQUAL qualification claims and demonstrates competence to employers.

Output: Competency matrix, evidence portfolio (downloadable), qualification readiness, career progression score.