Sander A.

Through Ardinois, I take on fractional CAIO and Head of Data & AI roles, stepping into enterprises to lead their data and AI agenda directly.

• Act as the senior Data & AI leader for organizations without one, owning strategy, operating model, and the path from pilots to production-grade AI.
• Set and drive the AI roadmap with C-suite and business leaders, prioritizing the use cases that move the P&L.
• Build the team, platform foundations, and governance needed to scale AI past experimentation into operations.
• Particular depth in retail and consumer.

As one of the world’s largest fashion companies with more than 132,000 employees, H&M offers fashion and quality at the best price across global brands and channels.

• Led a ~100-person global Data & AI organization, with cross-functional engineering oversight of a 400+ person environment.
• Deployed enterprise AI from concept to production across demand forecasting, inventory optimization, pricing, markdown, recommendations, and generative AI.
• Built scalable ML platforms and MLOps practices to shorten iteration cycles and improve production reliability.
• Partnered with merchandising, supply chain and digital teams to embed data-driven decisioning into retail operations.
• Member of the H&M Engineering Board, setting company-wide technical standards.

NIKE, Inc. is a purpose-driven organisation committed to moving the world forward through the power of sport; a global leader in athletic footwear, apparel and digital services.

• Built and owned a $100M+ EBIT AI portfolio across demand forecasting, close-out optimization, inventory, and personalization, tied to marketplace and digital growth.
• Scaled the regional AI function to 11 cross-functional teams across multiple European markets.
• Represented EMEA on Enterprise Data & Analytics and Global AI leadership teams.

• Managed ML engineering teams responsible for production model delivery, reliability and feature rollout.
• Introduced CI/CD for models, standardized model monitoring (drift, performance) and incident runbooks for ML failures.
• Partnered with product managers and data engineers to translate use cases into production-ready ML services.
• Coached engineers on reproducible training, model versioning and secure model serving patterns to reduce operational risk.

• Led the Data Platforms product area — defined roadmap, APIs and SLAs for data products consumed by analytics & ML.
• Delivered scalable ingestion, semantic layering and access patterns to reduce duplicate engineering across use cases.
• Prioritised platform investments that increased developer velocity and made AI capabilities easier to reuse across teams.
• Worked with security and compliance to operationalize data contracts, lineage and access control for sensitive datasets.

• At Dynasource Sander is responsible for building the data capabilities within the organization.
• Architect and build a data lake & platform on Microsoft Azure & Databricks (Spark, Kubernetes, Airflow, Azure Data Lake, Neo4J, Azure EventHubs)
• Help define the organization’s data strategy
• Build the data team
• Setup the data engineering practice in the organization
• Bring data science projects from POC to production
• Recommendation Engine
• Using NLP for building a knowledge graph
• Setup BI & reporting

We’re Ayvens, a global leader in sustainable mobility, committed to making mobility easy for our clients.

• Architected data platform solutions for fleet & mobility use cases (telemetry ingestion, vehicle lifecycle analytics).
• Designed ETL/streaming pipelines and storage patterns to support near-real-time telematics and maintenance analytics.
• Defined integration strategy between operational systems (leasing, CRM) and analytics layers to enable autonomous workflows.
• Advised on cloud migration, data governance and cost optimisation while keeping data privacy and regional requirements in focus.

• As senior data engineer at Cooblue, Sander helped the transition from traditional BI to modern data processing. Key projects:
• Set up a data lake using Cloud Storage on the Google Cloud Platform.
• Set up a data processing environment using Spark on the Google Cloud Platform.
• Build Spark jobs and data pipelines to perform analysis, and attribution of e-mail marketing campaigns.
• Integrate reporting into BigQuery.

• Operated as an independent Big Data architect and consultant delivering end-to-end platform and analytics designs.
• Designed data architectures and ETL/streaming pipelines for clients across retail and services; focused on resilience and observability.
• Delivered consultancy engagements covering data modelling, infrastructure selection and implementation roadmaps.
• Provided hands-on implementation support and mentored engineering teams on best practices for production ML and data ops.

• Design and develop an event driven monitoring and alerting application for the DSE Cassandra using an event driven architecture. (Scala, akka, Kafka, Docker ,DSE Graph, Docker, CI)
• Developing a graph database solution for a high throughput, low latency authentication API (Scala, Neo4J, DSE Graph, Gatling)
• Performance testing and optimization of NoSql solutions. (Gatling, DSE Cassandra, Neo4J)
• Consulting with other teams on the use of Cassandra and Graph Databases.

BigData Republic is a hands-on data consultancy that builds data applications, predictive models and platforms; a strategic partner helping organisations create impact and value with data and analytics.

• Built production-grade data pipelines and ML models for clients across retail, energy and public sector engagements.
• Implemented MLOps patterns (orchestration, testing, model promotion) to move experimental models into stable production.
• Delivered end-to-end solutions from data ingestion through feature engineering to serving and monitoring.
• Worked in small cross-functional teams to translate business problems into measurable analytics and ML outcomes.

EY provides consulting, assurance, tax and transaction services that help solve clients' toughest challenges and build a better working world.

• Advised clients on analytics-driven decision-making: translated business questions into analytics roadmaps and KPI frameworks.
• Delivered diagnostic analytics and advanced models to unlock efficiency and reveal cost or revenue opportunities.
• Supported clients in defining data strategy, target operating models and governance to operationalize insights.
• Worked closely with cross-functional stakeholders to embed analytics into process and change initiatives for measurable impact.

• As Junior Aviation consultant I worked on operations research and airport development projects.
• Key tasks:
• Use data science techniques on large sets and surveillance data sets to build predictive models and forecasting tools.
• Development and maintenance of an aircraft tracking system to analyze and store live ADS-B (aircraft surveillance) data