At a Glance
- Tasks: Lead and build the data function for a fast-growing beauty brand.
- Company: Join P.Louise, a £165m beauty brand with a dynamic culture.
- Benefits: Competitive salary, performance bonus, and staff discounts on products.
- Other info: Opportunity to work closely with senior leadership and drive strategic decisions.
- Why this job: Shape the future of data in a thriving business and make an immediate impact.
- Qualifications: Proven experience in building data functions and strong technical skills.
The predicted salary is between 63000 - 77000 £ per year.
LOUISE HEAD OF DATA Reports to: Callum Wilson, FD | Location: Manchester (Office-based) | Function: Data with Merchandising on stock, margin and range performance; and with Operations on fulfilment and logistics data.
Act as the senior data voice in the business, advising leadership on what to build next, what to fix, and where data can unlock commercial value.
Build and lead the data function as it grows, including scoping and hiring future team members as the remit expands.
CANDIDATE CRITERIA Essential Proven experience building a data function, data warehouse, or BI capability from the ground up, ideally within ecommerce, retail, or a fast-scaling consumer business.
Strong hands-on technical ability across data warehousing, ETL/ELT tooling, and BI/visualisation platforms (e. g.
SQL, dbt, Fivetran/Stitch, Looker/Power BI/Tableau, or similar).
Track record of automating manual reporting processes and driving adoption of self-serve dashboards across non-technical teams.
Experience integrating multi-channel ecommerce data (e. g.
Shopify, marketplaces, retail/wholesale, marketing platforms) into a unified reporting layer.
Excellent stakeholder management, able to work equally well with the FD, commercial leadership, and technical peers.
Commercially minded: able to translate data into insight and recommendations, not just dashboards.
Desirable Experience in a high-growth, multi-channel beauty, fashion, or consumer brand.
Familiarity with the specific platforms in P.
Louise's stack: Shopify, Tik Tok Shop, Klaviyo, Triple Whale, Xero, and 3PL/WMS systems.
Experience supporting board-level and investor reporting.
Line management experience, with the ambition to build and lead a team over time.
SUCCESS MILESTONES In the first 3 months: Full audit of current data landscape complete, with systems, data quality, and reporting gaps clearly documented.
Data warehouse architecture designed and agreed, with a clear implementation roadmap.
Quick-win automations identified and delivered for at least one high-value manual report.
In the first 6 months: Core data warehouse live, with key systems (Shopify, Tik Tok Shop, Boots, Klaviyo, Triple Whale, Xero) integrated.
Finance MI pack and trade meeting reporting substantially automated, reducing manual compilation time.
Ecommerce and Marketing dashboards live and in regular use by relevant teams.
In the first 12 months: P.
Louise has a data function it is genuinely proud of, trusted, fast, and embedded into how the business makes decisions.
Manual, spreadsheet-based reporting largely eliminated across Finance, Commercial and Marketing.
A data governance framework is in place and understood across the business.
A clear, agreed case made for the next phase of investment in the data function, whether that's tooling, capability, or headcount.
WHAT WE OFFER A genuinely greenfield opportunity to build the data function of a £165m beauty brand from scratch, with full leadership buy-in.
A highly visible seat at the senior leadership table, working directly with the FD and the wider SLT.
Competitive salary, commensurate with experience.
Performance-related bonus.
Staff discount on P.
Louise products.
A fast-moving, entrepreneurial culture where your impact is felt immediately.
Head of Data & Automation employer: P Louise
P Louise is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of Stockport. With a strong focus on employee growth, we provide ample opportunities for professional development and career advancement, particularly in the fast-paced beauty retail sector. Join us to be part of a passionate team dedicated to driving ecommerce success and making a significant impact in the US market.
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We think this is how you could land Head of Data & Automation
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We think you need these skills to ace Head of Data & Automation
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 P Louise, 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 P Louise. 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 P Louise
✨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 P Louise!
✨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.
