Adidas MANAGER PERFORMANCE & ADVANCED ANALYTICS ECOMMERCE 

Saudi Arabia, Riyadh Region, Riyadh 

788199132

PURPOSE & OVERALL RELEVANCE FOR THE ORGANIZATION

As the eCommerce Performance & Advanced Analytics Manager, you are responsible for delivering end-to-end analytical services and insights that drive performance across the full digital commerce landscape. This includes owning performance reporting, demand forecasting, and advanced analytics that uncover business opportunities and drive fact-based decision making.

You will work across all eCom channels (own site, app, partner platforms), partnering with business stakeholders to translate data into actionable strategies. You will also lead the development of machine learning models and advancedpipelines that support scalable analytics and automation.

eCommerce Performance & Forecasting Analytics

• Lead the full-cycle eCommerce performance reporting across multiple levels (article, category, channel), combining backend data pipelines with frontend dashboards.
• Develop structured analytics frameworks to measure and explain business performance, answer key questions, and guide decision-making.
• Translate analytical models into business-friendly tools and interfaces (e.g., PowerBI,self-servicenotebooks,AI agents, etc).
• Build, maintain and improve various business performance tracking and analytics dashboards, both frontend and backend
• Partner with eCombusinessteams to identify performance drivers and develop strategic actions based on insights.

Advanced Analytics & Forecasting

• Build and continuously enhance demand forecasting solutions at product, category, and channel level—integrating historical trends, business input, and statistical modeling.
• Design and implement advanced analytics use cases (e.g.markdown optimization,product similarity) to optimize business outcomes.
• Explore machine learningand AIapplications to enable proactive performance management and self-service analytics tools.

Data Engineering & Solution Management

• dataandanalyticsteams to align ondata models, pipelines, and tooling for scalable analytics delivery.
• Oversee the work of data engineering vendors to ensure reliable, efficient data preparation pipelines.
• Own the delivery of analytics-readyeComperformancerelated data (sellout, inventory, etc.).

KEY RELATIONSHIPS

• KOREA e-com team
• KOREA Function teams (Finance,Data & Analytics)
• Globalanalyticsteams(Digital analytics, Data & Analytics)
• External vendors

REQUISITE EDUCATION AND EXPERIENCE / MINIMUM QUALIFICATIONS

• Degree with focus in Statistics, Economics, Math, Data Science, Business or related field preferred, or equivalent combination of education and experience
• 4+ years of experience working in Digital Analytics, Data Analytics, Business Intelligence, Demand forecasting & planning, Data Science or equivalent experience
• Experience in demand forecasting, time-series modeling, and/orcommercial performance analyticsand reporting.
• Experience in e-commerce environment
• Strong hands-on experience in data processing, analytics, and machine learning using SQL, Python, PowerBI.

KNOWLEDGE & SOFT SKILLS

• Strong analytical problem-solving skills, with ability to break down complex questions into structured analysis, with clear and concise communication.
• Business acumen in an eCom or retail environment, ideally strong understanding and proven experience in digital and e-commerce analytics, with deep knowledge of multi-platform e-commerce ecosystems, KPIs, and performance optimization.
• Ability to work in cross-functional, multicultural teams and manage external vendors.
• Experience presentingsolutions orfindings to both technical and non-technical stakeholders.
• Self-driven, detail-oriented, and continuously curious about emerging analytics and AI solutions.

HARD SKILLS

• aster of analytics tools including SQL, Python, PowerBI
• Hands-on experience with big data platforms such as databricks, AWS or Azure and coding tools such as Jupyter Notebook, Git, etc.
• Familiar withsalesKPIs (gross sales, net sales, margin, etc.)
• Experience in forecasting and predictive models
• Experience in data engineering, esp. data modeling and pipeline building

• Plus would be considered:
  • Experience in building data science or machine learning models
  • Experience deploying ML models into operational pipelines or dashboards.
  • Experiencein financial planning and analytics, farmiliar with financial KPIs
  • Experience supporting merchandising, planning, or omnichannel strategy.
  • Vendormanagementand project managementskills.

• Fluent English both verbally and written