Role: Lead Digital Analyst
Contract: Permanent
Shift pattern: Part Time - 22.5 hours
Location: Nottingham
Closing date: 10th October
Recruitment Partner: Matthew Nelligan
About the role
Join Digital Analytics in Boots' Nottingham-based Digital team. We're looking for a Lead Digital Analyst who will develop and own analytical frameworks to deeply understand commercial performance and customer behaviour on our digital platforms. You will partner with cross-functional teams to apply advanced analytics on large datasets, driving better decisions and data-driven products.
Key responsibilities
Reporting to the Head of Digital Analytics, you will be a key leader within the Boots Digital team, creating the most compelling omnichannel beauty, health, and wellness experience in the UK. Your core mission is to ensure data-driven decisions by providing a deep understanding of our commercial performance and customer behaviour.
You will be the primary expert on our digital datasets, including Google Analytics, and will apply advanced analytics to uncover key insights. Your analysis will focus on critical business themes like customer acquisition, retention, and conversion with a lens on products and services, allowing you to identify patterns, causal factors, and predict future performance.
This is a hands-on role where you will be an active partner to partners. You will mature the business's data understanding by developing analysis, and improving dashboards and other data products. Your insights will directly influence daily tactical decisions and long-term strategic planning, driving tangible growth opportunities.
What you'll need to have
* Analytics Leadership: Lead the conversation on digital performance, providing clear insights on its drivers and recommending relevant next steps to eCommerce and commercial decision-makers. You will be responsible for translating complex data into clear, compelling narratives for non-technical stakeholders, including senior management. You will also act as a data coach and consultant for business stakeholders, promoting data literacy and a self-service analytics culture across the organization.
* Strategic Insight: Apply advanced analytical techniques to understand business performance and customer behaviour from a variety of disparate data sources. Your work will involve integrating and reconciling datasets with different definitions to provide a holistic view that enhances our ability to direct business strategy and justify investment. This also includes ensuring data collection and analysis practices are compliant with relevant data protection regulations (e.g., GDPR/UK GDPR).
* Bridging the Gap: Act as the key liaison between the Digital Trading team and the Digital Analytics function. You will share insights, methodologies, and best practices to maximize the value of our digital data investments across the business.
* Data Product Development: Support the analytics team's data engineering efforts by identifying and generating new datasets for dashboards and other data-driven products. You will help build the infrastructure that enables wider business use of data, with a focus on developing and implementing first-party data strategies to ensure continued analytical capabilities in a privacy-first world.
* Innovation & Problem-Solving: Proactively identify and develop opportunities where digital analytics can be leveraged with other datasets to solve customer pain points, improve user experience, and drive growth.
* Predictive Analytics & AI: Proactively enhance your data and analytics skills and stay abreast of the latest industry trends. This includes leveraging AI and machine learning tools to reduce the barrier to entry, improve efficiency, build predictive models, forecast outcomes, and uncover deeper insights to drive business growth.
It would be great if you also have
* Digital Analytics Expertise: A proven expert-level understanding and practical experience with Google Analytics 4 (GA4) or other digital analytics platforms. You should be able to configure, troubleshoot, and derive insights from complex digital datasets.
* Data Querying & Manipulation: Advanced proficiency in SQL, Python and/or Excel for data extraction, manipulation, and analysis from data warehouses (e.g., BigQuery, Databricks).
* Data Visualization & Business Intelligence: Extensive experience with data visualization tools such as Tableau, Power BI, or Looker Studio to create impactful dashboards and reports for various audiences.
* Complex Data Analysis: Proven ability to work with and synthesize insights from multiple large and complex datasets, particularly time-series data, to understand business performance and customer behaviour.
* Causal Analysis & Experimentation: Solid experience in framing business hypotheses, designing analytical experiments, and analysing the causal effects of business treatments (e.g., promotions, price changes, product ranging) on key metrics.
* Strategic Thinking: The ability to translate complex data findings into clear, actionable business recommendations that drive strategic and tactical decisions.
* Communication & Storytelling: Exceptional verbal and written communication skills, with a proven ability to provide the narrative on performance and present complex concepts to non-technical stakeholders, including senior leadership.
* Problem-Solving: Strong analytical and critical thinking skills, with the ability to proactively identify business questions and use data to find solutions.
* E-commerce & Business Acumen: A deep commercial understanding of e-commerce business models and the key factors that influence digital performance, such as price, promotion, and product availability.
* Stakeholder Management: Experience building strong relationships with a wide range of stakeholders, from technical teams to commercial directors, to influence decision-making and drive a data-driven culture.
* An understanding of statistical modelling, machine learning concepts, or experience with data languages like Python or R.
* An understanding of digital data production and collection, including tag management. Experience with data platforms such as Databricks or BigQuery.
* Prior experience working in a retail, e-commerce, or omnichannel environment.
* A strong background in a quantitative field such as mathematics, statistics, economics, or a related STEM discipline.
Our benefits
* Boots Retirement Savings Plan
* Discretionary annual bonus
* Generous employee discounts
* Enhanced maternity/paternity/adoption leave pay and gift card for anyone expecting or adopting a child
* Flexible benefits scheme including option to buy additional holiday, discounted gym membership, life assurance, activity passes and much more.
* Access to free, 24/7 counselling and support through TELUS Health, our Employee Assistance Programme.
We have a great range of benefits in addition to the above that offer flexibility to suit you - find out more at boots.jobs/rewards. Exclusions may apply, eligible roles only. Please note, any salary estimates given on third-party sites are not provided or endorsed by Boots and may not be accurate.
Why Boots
At Boots, we foster a working environment where consideration and inclusivity help everyone to be themselves and reach their full potential. We are proud to be an equal opportunity employer, passionate about embracing the diversity of our colleagues and providing a positive and inclusive working environment for all. As the heart of everything we do at Boots, with you, we change for the better.
What's next
Where a role is advertised as full-time, we are open to discussing part-time and job share options during the application process. If you require additional support as part of the application and interview process, we are happy to provide reasonable adjustments to help you to be at your best.
This role requires the successful candidate to complete a Pre-employment check after receiving an offer. Depending on your location you will be asked to submit either a DBS (Disclosure & Barring Service), PVG (Protection of Vulnerable groups) or an Access NI Check.
Boots is a Ban the Box employer and will consider the suitability of applicants with criminal convictions on a case-by-case basis.
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