At a Glance
- Tasks: Join a transformation programme to enhance data-driven decision-making using AI and Looker.
- Company: Dynamic organisation at the forefront of AI-enabled analytics in London.
- Benefits: Competitive daily rate, hybrid working, and opportunity to work with cutting-edge technology.
- Other info: Exciting role with opportunities for professional growth in an agile environment.
- Why this job: Shape the future of data analytics and make a real impact on business decisions.
- Qualifications: Experience with Looker, LLMs, and strong SQL skills required.
5-6 Month Contract
Up to £525 per day | Outside IR35
Hybrid Working - 1-2 Days Per Week Onsite
We are looking for an experienced Data Analyst to join an exciting transformation programme focused on evolving how the organisation uses data to drive better business decisions. This role will play a key part in enabling self-service analytics by leveraging Looker to create semantic layers across core datasets. These semantic models will support Looker AI Agents (Looker Conversation), Large Language Models (LLMs) and automated push notifications, giving business users greater flexibility to explore data, receive proactive insights and accelerate decision-making.
A significant focus of this role will be working with LLM-powered AI solutions, reviewing large and complex datasets, validating AI-generated outputs and ensuring that insights delivered to the business are accurate, reliable and fit for purpose. You'll be responsible for maintaining rigorous quality assurance standards and will have the confidence to sign off AI-generated outputs before they are released to the business.
Working closely with business stakeholders, data engineering teams and analytics specialists, you'll help shape how AI, semantic modelling and trusted data are used across the organisation.
- Key skills and responsibilities:
- Looker expertise - Proven hands-on experience developing and working within the Looker platform, including semantic layer creation and optimisation.
- Looker AI Agents - Experience working with or supporting AI Agents within Looker (Looker Conversation), helping to optimise semantic models and improve AI-generated responses.
- Automated Push Notifications - Experience building or supporting automated push notifications and proactive insight delivery using data-driven workflows.
- LLM & AI experience - Strong experience working with Large Language Models (LLMs), AI-powered analytics or conversational AI solutions, ensuring outputs are accurate, relevant and trusted.
- Large Dataset Analysis - Extensive experience analysing, interrogating and validating large, complex datasets, identifying anomalies and ensuring data integrity across AI-driven solutions.
- Semantic Layer Development - Collaborate with business domain experts to design, build and optimise semantic layers, working closely with Data Engineering to improve performance and scalability.
- Quality Assurance - Significant experience testing, validating and quality assuring data products and AI-generated outputs, with exceptional attention to detail and a critical eye for accuracy.
- Results Ownership - Confident taking accountability for data quality and formally signing off whether AI-generated insights meet business and delivery standards.
- AI & Machine Learning Lifecycle - Previous experience supporting AI/ML initiatives and AI agents from development through to deployment, with an understanding of model validation and continuous improvement.
- SQL Proficiency - Strong working knowledge of SQL for analysing, interrogating and validating large datasets.
- Stakeholder Engagement - Partner with business stakeholders to understand key business questions and translate requirements into trusted analytical models.
- Adaptability - Comfortable working in an agile environment where priorities evolve, AI capabilities mature and continuous learning is encouraged.
This is an exciting opportunity to work at the forefront of AI-enabled analytics, helping shape how the organisation leverages LLMs, Looker AI Agents, semantic modelling and automated push notifications to transform how data is consumed and trusted across the business.
Interested? Please submit your updated CV to Dean Sadler-Parkes at Harvey Nash for immediate consideration.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst - London
✨Tap into Online Data Science Communities
Join online communities focused on data science like Kaggle, LinkedIn groups, or Reddit threads. These are goldmines for temporary gigs, as you can network with professionals and potentially hear about opportunities at companies like Harvey Nash Group before they're even advertised!
✨Show Off Your Skills With Projects
Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.
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We think you need these skills to ace Data Analyst - London
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Harvey Nash Group, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to Harvey Nash Group, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab Harvey Nash Group’s attention and show the tangible impact of your work.
How to prepare for a job interview at Harvey Nash Group
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at Harvey Nash Group.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at Harvey Nash Group.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at Harvey Nash Group.
