At a Glance
- Tasks: Join a dynamic team to deliver impactful AI projects for top UK retailers.
- Company: Innovative company focused on AI transformation in retail.
- Benefits: Unlimited annual leave, private healthcare, flexible working, and coaching support.
- Other info: Diverse and inclusive environment with opportunities for personal growth.
- Why this job: Be at the forefront of AI innovation and make a real difference in retail.
- Qualifications: Experience in AI/data projects and strong communication skills.
The predicted salary is between 28800 - 48000 £ per year.
About the role
This is an exciting, new role for an individual motivated to build their knowledge of AI transformation in retail. As an Associate, you’ll be part of a close-knit team - scoping, building and delivering impactful AI projects for some of the largest retailers in the UK. We’ll look to you to build trusted client relationships, analyse requirements and feedback, stay on top of workflows and help to ensure our bespoke AI tools are optimised for real-world operations.
What you'll be doing
- Managing individual work streams to support the successful delivery and implementation of bespoke AI solutions.
- Working side-by-side with Retail and Consumer stakeholders to understand critical mission challenges and user needs.
- Conducting open-source analysis to support the development of cutting-edge AI tools.
- Translating complex operational requirements into clear user stories for delivery and engineering teams.
- Designing and testing workflows that support user-centric decision-making in high-stakes environments.
- Collaborating closely with technical teams to ensure projects run smoothly and solutions meet customer needs.
- Contributing to internal thought leadership, strategy, and capability development across the team.
Who we're looking for
- You demonstrate analytical thinking, can clearly communicate ideas, and synthesise complex information.
- You have some experience working on AI / data intensive projects in the retail and consumer sector.
- You’ve worked with technical teams.
- You understand Agile and related methodologies and the basis of iterative development and continuous delivery.
- You are thoughtful and proactive in ambiguous situations, keen to take initiative and own finding solutions to challenges.
- You’re excited and energised by the possibilities for innovation in retail and consumer technology!
Our interview process
- Talent Team Screen (40 mins)
- Introduction Interview (60 mins)
- Case Study Interview (60 mins)
- Interview with Business Unit Director (30 mins)
Our Recruitment Ethos
We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.
Some of our standout benefits
- Unlimited Annual Leave Policy
- Private healthcare and dental
- Enhanced parental leave
- Family-Friendly Flexibility & Flexible working
- Sanctus Coaching
- Hybrid Working (2 days in our Old Street office, London)
If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please do apply or reach out to our Talent Acquisition team for a confidential chat - Please know we are open to conversations about part-time roles or condensed hours.
Associate employer: Faculty
At Faculty, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As the Head of Banking AI Transformation, you will have the opportunity to lead transformative projects in a rapidly evolving sector while benefiting from our commitment to employee growth through continuous learning and development. Located in a vibrant area, our team enjoys a supportive environment that values diversity and encourages meaningful contributions to the financial services landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Associate
✨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 Faculty!
✨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 Associate at Faculty.
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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 Faculty.
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When you find a suitable opening like Associate at Faculty, 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 Associate
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 Faculty, 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 Faculty. 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 Faculty
✨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 Faculty!
✨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.
