Senior Manager, Data Analytics

Location: Greater London

## Senior Manager, Data Analytics Apply locations:
Greater London, G  (United Kingdom Corporate Office) time type:
Full time posted on:
Posted Todayjob requisition :
JR7950

Explore the possibilities across our global house of brands.

Defined by inclusivity rather than exclusivity, Tapestry embraces the exploration of individuality and invests in helping you grow personally and professionally. Every individual in our global house has the opportunity to make an impact, learn and be part of our growing and unique story.

At Tapestry, we have the freedom to express ourselves and run with our best ideas across Coach and Kate Spade New York. We share a profound belief in both our individual and collective potential, and know that with hard work and dedication, anything is possible.
** Primary

Purpose:

** The Senior Manager, Data Analytics applies advanced analytics and data science to fuel growth of Tapestry’s EMEAI markets. The focus is shifting from routine reporting to actionable insight, driving adoption of data-based measurement across the organization and championing automation and AI to accelerate decision making and operational efficiency. You will work collaboratively with business partners worldwide to define the right questions, uncover high impact opportunities and translate insights into practical business recommendations that improve revenue, gross margin and customer experience.
** The successful individual will leverage their proficiency in Data Analytics to:
*** Centralise data integrity, reporting, tools architecture and training while decentralising insight creation and action. Partner across functions to design data‐driven analysis, strategies and tools
* Shift effort from static reporting to insight generation. Build interactive visualisations, dynamic dashboards and standard reports that surface leading‐indicator insights
* Perform large‐scale analysis that uncovers high‐impact acquisition drivers, media‐spend efficiency and revenue‐boosting actions; translate results into clear, data‐driven stories
* Drive organisation‐wide adoption of data. Measure outcomes, showcase impact and encourage a data‐first mindset for decision‐making.
* Embed predictive models, automated reporting and AI‐driven recommendations (e.g., MAP efficiency, allocation optimisation) and champion their use in business processes
* Drive adoption of automation & AI. Lead AI/ML pilot projects, demonstrate tangible value and promote scaling of successful models
* Collaborate with data‐engineering, data‐science and algorithm teams to innovate data sourcing, management and product solutions
* Connect with the Global Data Analytics (DA) team to align reporting standards, share best practices and foster cross‐regional data collaboration
* Maintain data integrity, develop reusable analytics tools and provide stakeholder training so teams can rely on accurate self‐service data
* Track key operational metrics, measure operational efficiency and drive process improvements that maximise sales, gross margin and improve the site site‐consumer journey & conversion, and focus the organisation on acquisition levers
** The accomplished individual will possess:
*** 5+ years of hands‐on analytics experience within retail, eCommerce, or consulting environments
* Advanced SQL and ETL capabilities
* Strong data‐visualisation expertise (Tableau or comparable)
* Hands‐on experience with Google Analytics and Big Query
* Proficiency in Python or R for analysis and modelling
* Proven ability to drive adoption of data‐based measurement and turn metrics into strategic actions
* Demonstrated experience championing automation and AI (automated pipelines, predictive models, AI‐assisted tools)
* Excellent storytelling, communication, and relationship‐building skills
* Track record of translating analytics into revenue‐driving initiatives and improving gross margin
* Ability to prioritise dynamically in a fast‐paced, global environment
* Bachelor’s degree in a quantitative or technical discipline
* Experience deploying AI/ML solutions at scale (recommendation engines, demand forecasting, etc.)
* Familiarity with automation/orchestration platforms (Airflow, Prefect) and MLOps…