We are working alongside our major client, a huge multinational retail conglomerate with a head office in Dubai, to instill a Head of Business Intelligence & Analytics to supplement their thriving eCommerce operational team.
- Develop and implement strategy, data architecture and tools, business practices and operationally manage business intelligence, app and web analytics, and data science functions of eCommerce, across several retail verticals for top international brands, and several countries, across the Middle East, Russia, Turkey and Central and Eastern Europe in line with overall eCommerce business strategy and objectives.
- Responsible for eCommerce division Data & Analytics reporting and data architecture in rapidly growing eCommerce, online (and omnichannel) marketing and trading performance improvements across the business with special focus on Middle East market, that supports the overall P&L ecommerce divisional targets. Ensures goals and financial targets are defined, aligned and met by online trading teams in line with overall online and omnichannel business strategy.
- Design and implementation of overall reporting and analytics tools and architecture, including but not limited to product tracking and tag management solutions, web and mobile app analytics, conversion funnel and UI UX analysis, supports AB testing practices, marketing analysis performance and attribution, customer profiling and segmentation, dashboards and data visualization, customer intelligence, machine and deep learning techniques and algorithms, and data science.
- Develops data analysis and reporting services to support business decision-making that drives performance across all ecommerce brands, establishing best practices, working at all times closely with Online Trading, Online Marketing and Design & Content teams. Also works with brand directors and vice presidents to provide ecommerce business insight and reporting of online sales.
- Intimately understands web and app analytics, tagging, data acquisition (e.g. ETLs) and data processing processes, CRM, data visualization and data mining to drive insight.
- Analyses and builds understanding of regional consumer shopping behaviour to efficiently translates this to online shopping experience, in online merchandising and online marketing customer acquisition and retention. Leads customer insight, customer segmentation, driving personalization driving customer personalization, relevancy of products and offer, and targeting across websites across several brands and markets.
- Responsible for definition of analytics, BI and data science practices, business reporting tools and KPI definition and management, providing transparency and actionable insight that drives web traffic, conversion rate and average order value that supports sales target, profitability and ecommerce share-of business growth.
- Works closely and in partnership with senior eCommerce peer group, including online marketing performance acquisition and retention, web design and product content production, web development, online merchandising and buying, online marketing, and online operations.
- Recruits, develops, inspires and leads Ecommerce Analytics, BI and Data Science teams, creating a performance driven culture that promotes teamwork, innovation, continuous experimentation and group learning, and teams collaboration. Responsible for analytics, BI and data science teams, headcount and costs management across ecommerce.
- Together with Online Trading and Online Marketing, responsible for brands online business modelling and business planning. Together with VP of eCommerce, and other Head of functions defines trading plans, understanding business and trading dynamics, building reliable business financial models that project future business performance. Liaises Online Marketing to agree traffic models and retention curves, and Online Trading to agree online trading sales plans and margins.
- Data Tech & MarTech, Data Science, Data Product, Data Engineering/Testing, Business Analysis, Data Architecture & Quality, across different frameworks, including Google Stack.
- Experience and understanding in tools like Google GTM, GA360, Google Big Query, Azure Data Flow, Funnel.io, Adjust, Amplitude, Alteryx, Content Square, Trifacta, MS Power BI, Firebase, TensorFlow, and other similar Data tools.