Data Strategy for AI

Data and AI strategies that make AI possible: roadmaps, data foundations, AI Factory and operating models, investment priorities.

44 contributions across 7 experiences

Where this skill was applied

Often together withAI governance, risk & regulatory compliance Machine learning, deep learning & MLOps Innovation & change management Solution & enterprise architecture Generative AI & LLM solutions Data architecture, engineering & governance

2024–202513 contributions

EPAM Systems

Led the technical response to a Tier-1 Swiss bank’s enterprise AI RFI — structured on business value; technology, security and compliance; and people, operating model and governance — later reused as the technical core of a second pursuit with the same bank and the engagement behind EPAM’s preferred-vendor status.
Coordinated the proposal for a bank-wide Generative AI blueprint mapping 35 prioritised use cases across all seven divisions of the bank over six enabling layers: AI strategy, legal and compliance, data and security, technical architecture, responsible AI and workforce enablement.
Global agribusiness and food company, Switzerland: defined the GenAI strategy for shipping and transport optimisation, structuring 18+ use cases (laytime calculations, contract analysis, chartering risk mitigation) with OCR, NLP, LLMs and knowledge graphs.
Spearheaded the global expansion of EPAM’s Data & AI practice across EMEA, North America, APAC, LATAM and CIS, defining strategic direction for AI, Generative AI and Agentic AI, and led client engagements and pre-sales across banking, government services, logistics, consumer goods, biopharma, chemicals, telecommunications, energy and industrials.
Designed the technical questionnaire responses on model orchestration, multi-LLM integration, RAG, embedding strategies and secure deployment, articulating EPAM’s LLMOps approach, AI Factory and compliance measures, and coordinated contributions from global EPAM teams.
Adapted EPAM’s Generative AI Factory target architecture for the bank — three planes (Models / Data / Services) over Data Factory, AI Backoffice and AI Serving Platform — covering feature and prompt engineering, continuous training and evaluation, data- and model-drift monitoring, hallucination management, guardrails, vector stores, FinOps and a gateway to third-party models, closing on a dedicated data-privacy layer.
Major US county government: as principal AI/GenAI expert, spearheaded the response to an RFP for enterprise-wide AI and automation services — designed the global delivery model, defined the AI Factory approach and translated requirements into modular solutions for GenAI, automated document processing and operational decision support.
Global pharmaceutical company: principal expert (GenAI, architecture, software engineering) supporting the AI Factory framework and global AI strategy; defined a reusable AI component framework and LLM/multi-agent orchestration for biomedical R&D and regulatory processes, and a global Community of Practice for AI knowledge sharing.
Directed engagements in data engineering and cloud platforms, defining enterprise data-platform strategies on Snowflake, BigQuery and Synapse and advising on data contracts, service tiering and pipeline monitoring.
Leading telecom operator, Africa: co-led the RFP response on enterprise AI/GenAI strategy, developing a target-state federated AI architecture, AI Factory delivery capabilities and a GenAI integration roadmap.
Leading logistics and postal group, UK: designed a strategic MLOps assessment offering for enterprise-wide AI/ML adoption, with an evaluation methodology across data ops, model management and platform readiness.
Global coffee company, Netherlands: led the analytical assessment of predictive analytics for global shipment delays — historical shipping and customs data, key delay drivers, model performance — and delivered the resulting AI strategy and offering.
Established a production MLOps operating model: experiment tracking, feature management, model registry, reproducible pipelines, CI/CD, automated testing, deployment controls, rollback, monitoring and scheduled retraining.

2019–20246 contributions

DSM-Firmenich

Steering Committee member of the Corporate Research Program for Digital Transformation; co-authored the 2019 Digital Aiming Points for the global R&D digital strategy and contributed to the HR Talent Acquisition and Retention Strategy.
Founded and led the Digital Hub in Poland, an agile, start-up-like AI research group with proven cost savings of €650,000 per year, and designed its Talent Acquisition Strategy for Digital and Data Science with retention guidelines, cutting AI team turnover by 80%.
Led the development of a machine-learning model to reduce the causes of gas emissions in wastewater treatment plants for vitamins, providing concrete strategies for environmental impact reduction.
Designed the data governance strategy for R&D and manufacturing on the DAMA Body of Knowledge, with policies, FAIRness guidelines, quality standards and data stewardship aligned to the corporate digital strategy.
Developed the global strategy for adopting clinical-trial data standards, extending CDISC-SEND to animal nutrition research to enable rapid submission of results to the FDA.
Managed collaborations with Contract Research Organisations (CROs) for digital projects, establishing strategic partnerships for external AI/ML development and research.

20263 contributions

Gavi, the Vaccine Alliance

Aligns the Innovation Lab architecture and experimentation portfolio to Gavi 6 Strategy 2026–2030 “Data Visibility & Use”, so every experiment traces to programmatic impact on global immunisation delivery.
Member of the Gavi architecture board, responsible for standards, investment prioritisation, solution assurance, exception management and technology-risk decisions; set up and coordinates the Gavi Innovation Lab.
Supported the conversion of the Innovation Lab from a project team into a consumable internal service, defining five entry pathways by idea maturity, a guided intake routed on maturity, urgency and strategic alignment, and three graduated support levels; participated in the launch of the new Innovation Lab Office.

2025–20262 contributions

Solara28

Developed an ecosystem strategy covering payments, accounting and e-invoicing, logistics, local commerce associations, digital agencies and technology providers to accelerate merchant acquisition and operational integration.
Governed the automated delivery lifecycle — architecture, software engineering, testing, security, DevOps and documentation — as an agentic AI operating model aligned with the EU AI Act.

20182 contributions

Fair Trade Handels

Defined and executed the new digital and data strategy — resources, technology and architectures — leading organisational change and aligning processes and resources to the new direction.
Defined market-access and commercial analytics strategies, improving visibility across key markets and supporting increased product uptake.

2013–20181 contribution

Nespresso (Nestlé)

Implemented an A/B/n multivariate testing strategy that significantly improved campaign effectiveness and ROI, integrating sentiment analysis and topic modelling for actionable insights.

2002–20111 contribution

United Nations CGIAR

Led global initiatives across digital, data science, knowledge management and bioinformatics, progressing from Multimedia Web Specialist to Digital Unit Head with responsibility for strategic planning and implementation.

Profile12 contributions

Across the career

AI, Data and Technology Executive with 15+ years of international experience in artificial intelligence, Generative AI, machine learning, data strategy and enterprise transformation, combining executive-level AI strategy with hands-on technical leadership and principal engineering experience in AI and Generative AI.
Uses Solara28 as a concrete reference case for AI-native product strategy, operational efficiency, platform architecture and business-model innovation.
Specialises in Generative AI, LLMs, RAG, Agentic AI, predictive analytics, machine learning, MLOps, LLMOps, AI governance, AI factories and model evaluation; designs enterprise AI and data strategies and defines AI technology stacks and long-term machine-learning roadmaps through hands-on technical leadership.
Architects AI solutions that connect business objectives, data foundations, operating models, technical platforms, governance and measurable outcomes.
Specialises in data products and AI strategies for pharmaceutical, biotech, clinical-development and biomedical environments.
Works across clinical-trial data strategy, TMF metadata, CTMS, eTMF, EDC integration, clinical time-series and regulated data ecosystems, partnering with Contract Research Organisations (CROs) to align clinical-trial data with CTMS, eTMF and EDC systems.
Leads strategic client engagements from discovery and solution scoping through architecture, value proposition, proposal development and executive presentation, combining pre-sales acumen with client relationship management.
Advises C-level stakeholders on AI investment, data strategy, technology choices, operating models and transformation priorities.
Combines strategic data governance with hands-on architecture, pipeline design, integration, data modelling and platform implementation.
Connects technology strategy to business value, cost optimisation, operational efficiency, revenue growth, risk reduction and customer outcomes.
Translates ambitious strategy and complex technical possibilities into practical operating models, technology and delivery roadmaps, business cases, investment priorities, partnerships and measurable delivery outcomes.
Advises C-suite and senior leadership on data governance, AI, agentic AI operating models and workforce transformation, and mentors executive teams moving towards data- and AI-led organisations.

Skills4 contributions

Skills & applied knowledge

AI and Generative-AI technologies: GANs, LLMs, agentic AI, FinOps, Trustworthy AI, MLOps, LLMOps, AI Factory strategy, MCP, A2A, multi-agent systems and Azure AI Foundry.
R&D strategy and innovation-adoption practices in pharmaceutical and life-sciences organisations.
MLOps operating models, deployment practices, monitoring, automation and lifecycle governance.
Programme and project management, strategic direction, Agile delivery, Scrum, SDLC governance, security management, security standards and enterprise technology standards.

All skills

Artificial intelligence

AI governance, risk & regulatory compliance 81 Machine learning, deep learning & MLOps 53 Data Strategy for AI 44 Generative AI & LLM solutions 43 Agentic AI & AI-native engineering 29

Architecture & data platforms

Solution & enterprise architecture 62 Data architecture, engineering & governance 54 Semantic engineering & knowledge management 50 Cloud & multi-tenant SaaS platforms 41

Leadership & business

Innovation & change management 42 Team leadership & talent development 31 Business value & financial management 29 Programme, project & vendor management 27 Executive advisory & pre-sales 19 Entrepreneurship & venture building 13

Product, marketing & communication

Digital marketing & customer analytics 27 Product & full-stack engineering 23 Communication & thought leadership 10