At a Glance
- Tasks: Lead data analytics and AI projects to drive impactful business decisions.
- Company: Join RES, the world's largest independent renewable energy company.
- Benefits: Competitive salary, professional development, and a commitment to sustainability.
- Other info: Collaborative environment with opportunities to shape the future of analytics at RES.
- Why this job: Make a difference in climate change with your analytical skills and innovative solutions.
- Qualifications: 10+ years in analytics, strong Python and SQL skills, and experience with machine learning.
The predicted salary is between 80000 - 100000 Β£ per year.
- 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 β and the people working on them are extraordinary.
We're growing our data and AI capability and looking for someone who genuinely loves working with data, machine learning, and generative AI to solve hard business problems.
If you want your analytical work to drive real decisions β within a company that's changing the world β this is the role.
The Role
You'll own the delivery of analytics and AI products at RES β turning complex data into trusted, governed insight consumed by senior leaders and decision-makers across the business.
This is a hands-on technical role with 10+ years of experience required.
You'll build models, write Python and SQL, apply LLMs and machine learning to business questions, and deliver automation that cuts manual effort and unlocks new insight.
You'll focus your energy on analysis, AI application, and insight delivery β working with modern cloud platforms and pre-built data infrastructure than building pipelines from scratch.
Everything you deliver will be accurate, explainable, and appropriately governed.
- What Youβll Do
- Analytics & AI
- Deliver advanced analytics across complex business domains β defining, validating, and owning the metrics and models that drive decisions.
- Apply machine learning to real business problems: predictive modelling, classification, segmentation, anomaly detection, and forecasting.
- Use LLMs and generative AI to build analytical tools, AI-assisted insight products, and intelligent automation β including prompt engineering and retrieval-augmented generation (RAG).
- Validate all AI and model outputs for accuracy, bias, and reliability before they reach stakeholders.
- Translate analytical findings into clear, business-ready insight for senior and executive audiences.
- Automation
- Identify and deliver automation opportunities using tools such as Power Platform, Power Automate, or equivalent β reducing manual effort and improving data-driven workflows.
- Use Python and SQL to clean, model, and analyse data; deliver self-service analytics through governed semantic models and reporting layers.
- Governance & Responsible AI
- Apply data classification, access controls, and quality standards to all analytical outputs.
- Embed responsible AI principles β fairness, explainability, and appropriate use β into every solution you deliver.
- Stakeholder Delivery
- Lead UAT and business validation for analytics outputs and AI products.
- Work closely with business stakeholders to understand problems, shape analytical approaches, and land insight in a way that drives action.
- Support teams in moving from manual reporting to governed, AI-enabled analytics.
- What Youβll Bring
- Python and SQL β strong, hands-on proficiency for data analysis, modelling, and scripting.
- Machine learning β practical experience building and applying supervised and unsupervised models to real business problems.
- Generative AI and LLMs β prompt engineering, RAG, and applied use of LLM tooling in an analytical context.
- Automation tooling β experience with platforms such as Power Platform, Power Automate, or equivalent.
- Data visualisation β ability to design clear, accurate, executive-ready outputs using tools such as Power BI or equivalent.
- Responsible AI β experience applying fairness, explainability, and governance principles to analytical products.
- Stakeholder communication β confident translating complex technical findings into plain language and actionable recommendations.
- Your Background
Essential
- Degree in data science, data analytics, computer science, statistics, or a related field β or equivalent hands-on experience.
- 10+ years' experience as a technical analyst, delivering advanced analytics and AI solutions with measurable business impact.
- Strong Python and SQL skills applied in a real analytical context.
- Proven experience applying machine learning and/or generative AI tools to business problems.
- Solid understanding of data governance, quality, and responsible AI principles.
- Track record of working with senior stakeholders to translate complex data into business decisions.
- Experience with automation and analytics tooling β for example Power Platform, Power Automate, or equivalent.
- Familiarity with cloud data platforms such as Microsoft Azure, Fabric, or equivalent.
Desirable
- Experience working across multiple business domains or in a centre of excellence / shared analytics function.
- Relevant certifications in AI/ML, data science, Power BI, Microsoft Azure, or data governance.
Why RES?
- Work that matters β your analysis will inform strategic decisions 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 analytics and AI evolves at RES.
- Competitive salary, benefits, and commitment to your professional development.
- #J-18808-Ljbffr
Data Analytics and AI Technical Lead in Gateshead 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.
StudySmarter Expert Adviceπ€«
We think this is how you could land Data Analytics and AI Technical Lead in Gateshead
β¨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!
β¨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 Data Analytics and AI Technical Lead at RES.
β¨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.
β¨Apply Directly through Our Website
When you find a suitable opening like Data Analytics and AI Technical 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 doesnβt love a direct application? Itβs easier than navigating through job boards!
We think you need these skills to ace Data Analytics and AI Technical Lead in Gateshead
Some tips for your application π«‘
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. Donβt 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 youβre 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
β¨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!
β¨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, itβll really make us stand out!
β¨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!
β¨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how weβd 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.