Data scientist | retail

About the Role

Based in our Dubai Head Office at Festival City and reporting to the Head of Analytics. The objective of the role is to contribute to the retail divisions Analytics strategy with a strong focus on delivering insights for retail brands. Your role would be to farm out customer insights by analysing & segmenting data. Formulate campaigns to drive incremental revenue and build the everlasting connect with our customers through personalization. Assists the Retail Division in the development and implementation of campaigns to drive relevance within the different market.  Execute a clear plan for growth and development of Al Futtaim Retail customer base across the different brands, and strengthen value of the over-arching Analytics strategy. 

As a Data Scientist within Retail Analytics team the role holder will be responsible for select countries/brands to support the overall analytics strategy.

• He/ She will provide consultative approach, including advisory recommendations to support proposed analytics solutions & possess technical aptitude to solve complex big data business problems.
• Role holder needs to apply data analysis & statistical techniques to large data-sets related to our member behaviours in conjunction with transactional and other interaction data to analyse and interpret actionable insights to drive business results
• Review customer data for trends, patterns and causal analysis to assist brands and divisions in understanding customer behaviour cross brand and category.
• Review customer data for trends, patterns, and casual analysis to assist Brands in understanding customer’s activity.
• Perform profiling, exploratory and deep dive analysis on brand’s customer and transaction data to determine quality and usefulness of available information.
• Build new predictive models and establish methods of evaluating models to identify when they will need to be redeveloped.
• Perform post-hoc (correlational) analysis when experimental designs (causational analyses) are not feasible and explain the limitations of the results.
• Analyze the results of experiments (e.g. A/B testing for campaigns), presents results to business leaders, and provides advice/recommendations.
• Assists in ensuring data integrity and quality are maintained.
• Performs extensive data processing and analysis tasks on large-scale, long term projects that benefit the entire business.
• Advice business units of appropriate marketing actions based on the relevant information to ensure maximum return on campaign investment
• Partner with the other Statistical Analysts / Data Scientists to brainstorm and develop strategies for how to solve challenging problems when needed.
• Provide a detailed and complete understanding of customer bases across all Retail Brands leveraging the CRM Platform and the Single View of the Customer.
• Present findings to management in a language that can be readily understood by non-analysts.
• Perform and support marketing campaign analysis to determine business impacts and design , enhance, and distribute marketing reports that clearly communicate business results
• Identify opportunities to drive customer value through loyalty activities at Retail and Brand level.
• Provide Marketing and business units with models (both segmentation and propensity) to aid targeting and understanding of customer behaviour across businesses and Brands
• Guide the Data Analysts /statisticians to solve business use cases & ensure the delivery timelines are met

About the Requirements

• Mathematics and/or Statistics or Computer Science /Business Management degree or higher with at least 5 years’ previous work experience within Insight/Analytics space
• Previous experience working as an Analytics expert with a strong business acumen focussed on delivering Customer Analytics / Promotion Optimization / Pricing recommendations - in Retail /CPG/consulting space
• Strong understanding of data mining techniques, statistical concepts and predictive modelling. (e.g., neural networks, multi-scalar dimensional models, logistic regression techniques, machine-based learning)
• Experience with Big Data technologies (eg. Hadoop, Cassandra, Hive, or similar) and large Data Warehouse implementation (Oracle, SAP Hana, or similar)
• Experience in Reporting architectures (eg. SAS, Micro-Strategy, Oracle, SAP BO, Pentaho, Tableau and Cognos, Google Analytics, CoreMatrix, or similar)
• Experience with predictive analytics tools (eg. SAS, SPSS, MATLAB, or similar)
• Experience in CRM Modelling, Analytics & Campaign Execution (eg. MS Dynamics, SAS, Unica, Teradata, Oracle, or similar).