At a Glance
- Tasks: Unlock insights from consumer data to drive brand strategy and engagement.
- Company: Join a leading brand in the spirits industry with a focus on innovation.
- Benefits: Enjoy competitive pension contributions, private healthcare, and generous product discounts.
- Other info: Flexible hybrid working and excellent career development opportunities await you.
- Why this job: Make a real impact by transforming data into actionable insights for top brands.
- Qualifications: Experience in data science, strong analytical skills, and proficiency in SQL.
The predicted salary is between 50000 - 65000 £ per year.
Benefits
- Save for retirement and invest in your future - pension contributions (employee up to 8.75%, employer up to 14%)
- Share in our success with up to 10% Share Reward scheme (subject to eligibility)
- Private medical insurance that covers the cost of private healthcare and includes round the clock access to GP services and menopause health line
- 24/7 support for you and your loved ones to counselling, life coaching and information on financial, mental, and physical wellbeing
- Experience our exceptional brands with a generous annual product allowance, plus at least 20% discount in our staff shop
- Embrace work‑life harmony with hybrid working, 26 weeks’ paid maternity, paternity and adoption leave, and up to five paid carers leave days a year
Embrace Excellence
This role exists to unlock value from Edrington’s consumer data by transforming it into actionable insight that informs brand strategy, consumer engagement, personalisation and business decision‑making. Sitting within Digital Technology, the Data Scientist - Consumer Data will lead advanced analytics and data science activity across multiple brands, with The Macallan as the primary focus, while also supporting Highland Park, The Glenrothes and Brugal as priority brands within scope. Working closely with Marketing, Consumer Insight, CRM and wider Digital & Technology teams, the role will mine, model, analyse and interpret complex consumer datasets, develop predictive and prescriptive insights, and help evolve Edrington’s consumer data capability as part of a modern product‑led technology organisation.
Make an Impact
- Apply advanced analytics and data science techniques to consumer data across Edrington brands
- Analyse complex, multi‑source datasets to identify consumer behaviour, patterns and opportunities
- Generate actionable insight to inform consumer engagement, CRM strategy, personalisation and proposition development
- Design, build and maintain predictive and prescriptive models (e.g. propensity, Next Best Action, lifetime value, engagement forecasting)
- Develop and maintain consumer segments and personas enriched through behavioural data
- Design and evaluate experiments (e.g. A/B testing, uplift modelling) to assess effectiveness and incrementality
- Develop and maintain dashboards and analytical outputs to track consumer engagement and CRM performance
- Define and standardise KPIs and measurement approaches across brands and markets
- Work with engineering and platform teams to shape scalable, reusable consumer data models and pipelines
- Contribute to the development of curated, governed datasets for analytics and reporting
- Identify opportunities to improve data capture, instrumentation and enrichment
- Evaluate emerging analytics, data science and AI capabilities and recommend adoption where appropriate
Your Talent And Skills
- Proven experience in data science or advanced analytics roles using consumer or customer data
- Strong analytical and statistical capability with experience delivering actionable business insight
- Experience building predictive models that support operational decision‑making
- Advanced SQL capability and experience working with analytical data platforms
- Strong ability to communicate complex analysis to non‑technical stakeholders
- Practical understanding of data governance, data quality and responsible data use
- Experience supporting CRM, marketing analytics or personalisation use cases
- Familiarity with consumer data platforms (CDP / CRM ecosystems)
- Python or R for analytics and modelling
- Power BI or equivalent data visualisation tools
- Statistical modelling, machine learning and experimentation
