Graduate: Sustainability Data Analyst

Clerkenwell
1 month ago
Applications closed

Related Jobs

View all jobs

Graduate Data Scientist

Graduate Data Engineer

Graduate Clinical Data Analyst

Graduate Quantitative Researcher

Snowflake Data Engineer

Graduate Data Analyst: Client Solutions & Growth

Graduate: Sustainability Data Analyst
London office based
Candidates with a research-heavy degree, internship experience, Power BI courses, or applied analytics in their studies will stand out.

Summary of the Role
This role is essential in supporting the central Group Environmental function by diligently gathering, cleaning, analyzing, and presenting environmental and resource-related data collected from various global projects. The specialist will establish the fundamental measurement and tracking capabilities required for informed strategic planning, investment justification, and senior leadership reporting across the organization.

Key Requirements

Experience Level: Strictly for candidates at the graduate/entry-level (submissions must reflect this experience band).
Compensation: The remuneration package is competitive for a starting role in this field.
Candidate Profile: Data Specialist
A highly disciplined, proactive, and curious entry-level analyst who thrives on research, structured data handling, and methodical problem-solving. This individual will be responsible for:

Sourcing activity data from vendors, site managers, and global project teams.
Maintaining and cleaning the central environmental data repository.
Generating standardized impact reports (e.g., carbon footprint).
Transforming raw data into clear, actionable dashboards and insights.
🎓 Academic and Technical Foundation

Education: A degree in a relevant discipline where quantitative research, statistical interpretation, or data management was a core component (e.g., Environmental Science, Data Analytics, Economics, Geography).
Data Analysis: Foundational experience (from academia or projects) in data analysis.
Data Visualization Tools: Basic to intermediate familiarity with a data visualization tool (e.g., dashboard creation, simple data structuring, model organization).
Core Tools: Proficient in spreadsheet software, managing data logs, cleaning datasets, and following structured workflows.
Environmental Awareness: A genuine motivation to work in the environmental field and an awareness of major global standardized sustainability frameworks.
✨ Core Competencies

Stakeholder Liaison: Ability to professionally follow up with vendors, site teams, and regional offices for data, maintaining positive relationships while navigating varying levels of regional capability.
Organizational Rigor: Exceptionally structured, capable of accurately managing data requests, tracking follow-ups, logging submissions, and adhering to strict timelines.
Data Quality Assurance: Comfortable working with inconsistent or incomplete datasets and applying the discipline needed to bring them to an auditable standard.
Analysis and Insight: Able to interpret quantitative data, build fundamental visualizations, and calculate basic performance metrics (e.g., impact per unit of output or attendance).
Communication: Clear communicator, able to proactively escalate potential risks and present early findings in a simple, logical format to collaborators.
Proactivity: Approaches tasks with a proposed solution or approach first (e.g., "Here is my proposed method—does this align with the objective?").

Eligo Recruitment is acting as an Employment Business in relation to this vacancy. Eligo is proud to be an equal opportunity employer dedicated to fostering diversity and creating an inclusive and equitable environment for employees and applicants. We actively celebrate and embrace differences, including but not limited to race, colour, religion, sex, sexual orientation, gender identity, national origin, veteran status, and disability. We encourage applications from individuals of all backgrounds and experiences and all will be considered for employment without discrimination. At Eligo Recruitment diversity, equity and inclusion is integral to achieving our mission to ensure every workplace reflects the richness of human diversity

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.