Senior Data Insight Analyst

This senior role leads complex statistical and analytical initiatives that drive omni-channel growth, loyalty programme performance, personalisation strategy, and digital marketing optimisation. You will apply advanced modelling techniques and experimentation frameworks to shape customer experiences and influence strategic decisions across grocery retail and eCommerce.

The core responsibilities for the job include the following:

Advanced Statistical Modelling and ML Support:

• Lead sophisticated modelling initiatives, including multivariate and logistic regression for driver analysis, survival analysis for churn forecasting, and uplift modelling for retention and offer targeting.
• Marketing attribution and MMM (Marketing Mix Modelling).
• Clustering using advanced approaches (mixture models, DBSCAN).
• Develop features and oversee model evaluation using statistical rigour (AUC, lift curves, and ROC).

Customer and Marketing Science Leadership:

• Drive customer lifecycle and behavioural analytics across acquisition, activation, loyalty engagement, and retention.
• Lead design and analysis of personalisation routines (next-best-action, recommendation ranking, and offer targeting).
• Conduct promotional and pricing optimisation analyses using elasticity modelling and constrained optimisation techniques.

Experimentation Strategy and Causal Methods:

• Oversee A/B and multivariate experimentation programmes using advanced causal inference (CUPED, diff-in-diff, synthetic controls).
• Provide experimentation strategy to product managers and marketing leads, ensuring strong statistical governance.

Omnichannel and eCommerce Insights:

• Analyse digital shopper journeys across search, product discovery, cart behaviour, and fulfilment paths.
• Integrate insights from store, digital, loyalty, and marketing channels to provide executive-level recommendations.

Leadership and Influence:

• Present insights to senior leadership, influencing eCommerce, merchandising, and loyalty strategy.
• Mentor and manage junior/advanced analysts on statistical methods, experimentation design, and storytelling.
• Establish best practices and analytical standards across the team.

Requirements:

• Bachelor's or master's degree in a quantitative field such as statistics, data science, applied mathematics, or computer science.
• 4-6 years of analytics experience with significant exposure to e-commerce, digital marketing, loyalty programmes, or omnichannel retail.
• Expert SQL skills and significant experience with large datasets in Snowflake, Databricks, or similar platforms.
• Strong proficiency in Python (pandas, scikit-learn, statsmodels) for modelling, feature engineering, and evaluation.
• Extensive experience in statistical modelling, time-series forecasting, clustering, and optimisation.
• Deep familiarity with marketing analytics (attribution modelling, MMM, incrementality, and campaign effectiveness).
• Proven ability to present complex statistical results to executives and guide strategic decisions.