People & Culture Data Analytics and AI Lead in Larne

People & Culture Data Analytics and AI Lead in Larne

Larne Full-Time 70000 - 85000 £ / year (est.) Home office (partial)
RES

At a Glance

  • Tasks: Lead data analytics and AI projects to transform workforce insights at RES.
  • Company: Join RES, the world's largest independent renewable energy company.
  • Benefits: Competitive salary, benefits, and a commitment to your professional growth.
  • Other info: Collaborative environment with opportunities to shape P&C analytics.
  • Why this job: Make a real impact in the fight against climate change through data-driven decisions.
  • Qualifications: Experience in Python, SQL, machine learning, and responsible AI principles.

The predicted salary is between 70000 - 85000 £ per year.

  • Description
  • P&C Data Analytics and AI Technical Lead
  • Description

P&C Data Analytics and AI Technical Lead Make Power for Good RES is the world's largest independent renewable energy company.

Our mission is simple: a future where everyone has access to affordable, zero-carbon energy.

The problems we’re solving are among the most important of our generation — and the people working on them are extraordinary.

We’re growing our People & Culture data capability and looking for someone who genuinely loves working with data and AI to answer hard questions about people and organisations.

If you want your analytical work to have real business impact — within a company that is changing the world — this is the role.

The Role

You'll own the delivery of P&C analytics and AI products at RES — turning complex workforce data into trusted, governed insight consumed by P&C leaders, the Executive Committee, and the Board.

What You'll Do

This is a hands-on analytical role.

You'll build models, write Python and SQL, apply LLMs and machine learning to workforce questions, and deliver automation that cuts manual effort across P&C.

You'll work with pre-built data pipelines and a modern Azure platform, focusing your energy on insight, analysis, and AI application — not infrastructure.

Everything you build will handle sensitive employee data with the rigour, privacy controls, and ethical care it demands.

  • Analytics & AI
  • Deliver workforce analytics across headcount, attrition, absence, recruitment, diversity, and workforce planning — defining, validating, and owning the metrics that matter.
  • Apply machine learning to P&C use cases: attrition prediction, workforce segmentation, flight risk modelling, and talent insights.
  • Use LLMs and generative AI to build analytical tools and AI‑assisted insight — designing prompts, applying RAG approaches, and ensuring outputs are accurate, fair, and explainable.
  • Validate all AI‑generated outputs for accuracy, bias, and sensitivity before they reach business stakeholders.
  • Automation
  • Build automation workflows using tools such as Power Platform, Power Automate, and Dataverse — or equivalent — to reduce manual effort across P&C processes.
  • Use Python and SQL to clean, model, and analyse workforce data; deliver self‑service analytics through governed semantic models.
  • Governance & Responsible AI
  • Apply data classification, access controls, and privacy standards to all P&C analytical outputs.
  • Ensure AI tools operate only on approved, appropriately scoped data; embed responsible AI principles in everything you deliver.
  • Stakeholder Delivery
  • Lead UAT and business validation for P&C analytics outputs and AI products.
  • Support P&C stakeholders in moving from manual reporting to governed, AI-enabled analytics — translating technical outputs into clear business insight.
  • What You'll Bring
  • Python and SQL — comfortable using both for data analysis, modelling, and automation scripting.
  • Machine learning — practical experience applying supervised and unsupervised methods to real analytical problems.
  • Generative AI and LLMs — prompt engineering, applied use of LLM tools, and an understanding of responsible AI in a sensitive data context.
  • Automation tooling — experience with platforms such as Power Platform, Power Automate, or Dataverse to reduce manual effort across business processes.
  • Data visualisation — ability to design clear, executive-ready outputs using tools such as Power BI or equivalent.
  • Workforce analytics — understanding of core P&C metrics and how to interpret people data meaningfully.
  • Responsible AI — experience applying fairness, explainability, and privacy principles in an analytical context.
  • Stakeholder communication — confident translating technical findings into plain language for non-technical audiences.
  • Your Background

Essential

  • Degree in data science, data analytics, statistics, or a related field — or equivalent hands‑on experience.
  • Proven analytical experience delivering actionable insight from complex datasets with measurable business impact.
  • Practical Python and SQL skills used in an analytical context.
  • Experience applying ML models and/or generative AI tools to real business problems.
  • Solid understanding of data privacy, sensitivity, and responsible AI principles.
  • Experience working with business stakeholders to translate analytical outputs into decisions.
  • Experience with Microsoft automation and analytics tooling — for example Power Platform, Power Automate, or equivalent.

Desirable

  • Experience with HR or workforce platforms such as Workday, SAP Success Factors, or equivalent.
  • Experience in a sensitive data environment — HR, finance, health, or similar.
  • Relevant certifications in AI/ML, Power BI, Microsoft Azure, or data privacy.

Why RES?

  • Work that matters — your analysis will inform decisions at Ex Co and Board level in a company actively fighting climate change.
  • A modern, cloud-first analytics stack with genuine investment in AI tooling.
  • A collaborative, growing data function with real scope to shape how P&C analytics evolves at RES.
  • Competitive salary, benefits, and commitment to your professional development.
  • #J-18808-Ljbffr

People & Culture Data Analytics and AI Lead in Larne employer: RES

At RES, we pride ourselves on being an excellent employer, offering a dynamic work culture that fosters collaboration and innovation in the renewable energy sector. As a Solar Asset Monitor, you will benefit from comprehensive training opportunities, a supportive team environment, and the chance to contribute to sustainable energy solutions while enjoying a flexible work schedule. Our commitment to diversity and employee growth makes RES a rewarding place to build your career in the thriving UK solar industry.

RES

Contact Details:

RES Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land People & Culture Data Analytics and AI Lead in Larne

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like RES!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like People & Culture Data Analytics and AI Lead at RES.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like RES.

Apply Directly through Our Website

When you find a suitable opening like People & Culture Data Analytics and AI Lead at RES, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace People & Culture Data Analytics and AI Lead in Larne

Python
SQL
Machine Learning
Generative AI
LLMs (Large Language Models)
Prompt Engineering
Data Visualisation

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at RES, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at RES. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at RES

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at RES!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.