DIRECTOR DATA SCIENCE

PURPOSE & OVERALL RELEVANCE FOR THE ORGANIZATION

As a Director Data Science within Global Digital Analytics, you lead the Data Science capability powering the Trading product domain—specifically supporting the Pricing and Forecasting value streams. You are accountable for setting the strategic direction and quality bar for applied analytics, machine learning and product optimization, ensuring they deliver measurable business impact and are scalable across markets and platforms.

Together with your peer value stream leaders, you define a clear product roadmap and deliverables which are in sync with organizational needs, scale, timelines, funding and the team capacity. You establish and enforce standards for model governance, documentation, reproducibility, and Responsible AI, while translating complex requirements into clear roadmaps, backlogs, and adoption playbooks.

Additionally, through your proven experience, you guide the enablement and integration of Data Science products into our agentic AI ecosystem —so market teams can access trading capabilities through a unified, natural-language interface (agents). You mentor and coach the team towards the agentic world by embedding agentic patterns (tool use and workflow orchestration, RAG grounding, guardrails, and automated evaluation/regression gates) and by ensuring solutions are production-ready, explainable, auditable, and aligned with enterprise security and governance expectations.

KEY RESPONSIBILITIES

ANALYTICS

• Evaluates the need for analytics, assesses the problems to be solved and what internal or external data sources to use or acquire.
• Specifies and applies appropriate mathematical, statistical, predictive modelling or machine-learning techniques to analyze data, generate insights, create value and support decision-making.
• Manages reviews of the benefits and value of analytics techniques and tools and recommends improvements.
• Contributes to the development of analytics policy, standards and guidelines.

BUSINESS ANALYSIS

• Takes responsibility for investigative work to determine business requirements and specify effective business processes, through improvements in information systems, information management, practices, procedures, and organization change.
• Selects, adopts and adapts appropriate business analysis methods, tools and techniques; selecting appropriately from predictive (plan-driven) approaches or adaptive (iterative/agile) approaches.
• Collaborates with stakeholders at all levels, in the conduct of investigations for strategy studies, business requirements specifications and feasibility studies.
• Prepares business cases which define potential benefits, options for achieving these benefits through development of new or changed processes, and associated business risks.

CONSULTANCY

• Takes responsibility for understanding client requirements, collecting data, delivering analysis and problem resolution.
• Identifies, evaluates, and recommends options, implementing if required.
• Collaborates with, leads and facilitates stakeholder groups, as part of formal or informal consultancy agreements.
• Seeks to fully address client needs, enhancing the capabilities and effectiveness of client personnel, by ensuring that proposed solutions are properly understood and appropriately exploited.

DATA MODELLING AND DESIGN

• Investigates corporate data requirements, and applies data analysis, design, modelling, and quality assurance techniques, to establish, modify or maintain data structures and their associated components (entity descriptions, relationship descriptions, attribute definitions).
• Provides advice and guidance to database designers and others using the data structures and associated components.

EMERGING TECHNOLOGY MONITORING

• Leads systematic scouting, evaluation, and adoption of emerging technologies in Generative AI, foundation models, vector databases, and agent frameworks.
• Translates emerging trends into actionable technology roadmaps, reference architectures, and experimentation guidelines.
• Ensures that new technologies are introduced with clear governance, risk assessment, and production-readiness criteria.

AGENTIC AI & GENERATIVE AI PLATFORMS

• Designs cross-organizational frameworks for AI-agent reusability and interoperability, enabling agents built with different ecosystems (e.g. LangChain, LangGraph, LlamaIndex, Haystack, CrewAI) to integrate consistently through shared interfaces and protocols.
• Establishes best practices for agent design, including tool use, workflow orchestration, multi-agent coordination, memory management, grounding via RAG, guardrails, and automated evaluation/regression pipelines.
• Chairs and drives cross-departmental good-practice initiatives to institutionalize governance, Ways-of-Working charters, and coding standards for GenAI and agentic systems.
• Oversees the design of shared libraries and frameworks (e.g. modularity or composability assessment frameworks) to increase development efficiency and code reuse across global data science communities.
• Ensures all GenAI and agentic solutions are secure, auditable, explainable, and compliant with Responsible AI, data privacy, and enterprise security standards.
• Guides teams in productionizing agentic solutions using modern platforms and tooling, such as cloud-native ML stacks, CI/CD for ML, model and prompt versioning, vector stores, and observability tooling.

PROGRAMMING/SOFTWARE DEVELOPMENT

• Provides technical leadership on the design and review of complex, production-grade software and ML systems, including LLM-powered services, agent backends, APIs, and data pipelines.
• Ensures consistent use of modern software engineering practices across Python-based ML stacks, including testing, observability, version control, and infrastructure-as-code.
• Leads architectural reviews for AI systems spanning model development, orchestration layers, and integration into enterprise platforms.

RELATIONSHIP MANAGEMENT

• Implements stakeholder engagement/communications plan.
• Deals with problems and issues, managing resolutions, corrective actions, lessons learned and the collection and dissemination of relevant information.
• Collects and uses feedback from customers and stakeholders to help measure effectiveness of stakeholder management.
• Helps develop and enhance customer and stakeholder relationships.

REQUIREMENTS DEFINITION AND MANAGEMENT

• Defines and manages scoping, requirements definition and prioritization activities for small-scale changes and assists with more complex change initiatives.
• Follows agreed standards, applying appropriate techniques to elicit and document detailed requirements.
• Provides constructive challenge to stakeholders as required.
• Prioritizes requirements and documents traceability to source.
• Reviews requirements for errors and omissions.
• Provides input to the requirements base-line.
• Investigates, manages and applies authorized requests for changes to base-lined requirements, in line with change management policy.

SPECIALIST ADVICE

• Acts as a trusted expert and advisor on advanced analytics, machine learning, GenAI, and AI-agent architectures, consolidating expertise from internal and external sources.
• Provides definitive guidance on trade-offs between modeling approaches, agentic vs. non-agentic solutions, and build-vs-buy decisions for AI platforms.
• Promotes knowledge sharing and technical excellence through communities of practice, internal standards, and mentorship.

RESEARCH

• Builds on and refines appropriate outline ideas for the evaluation, development, demonstration and implementation of research.
• Contributes to research goals and funding proposals.
• Collects and analyses qualitative and quantitative data as required.
• Creates research reports to communicate research methodology, findings and conclusions.
• Presents papers at conferences, contribute significant sections of material of publication quality, and presents reports to clients.
• Contributes to research plans and identifies appropriate opportunities for publication and dissemination of research findings.
• Makes an active contribution to research communities.

IF REQUIRED: PEOPLE MANAGEMENT / RESOURCE MANAGEMENT

• Supports resource planning and may have full responsibility in recruiting process.
• Implements resource plans, including conducting recruitment interviews.
• Facilitates selection, assessment and on-boarding processes, and internal resource allocation.
• Contributes to transitioning of resources, complying with relevant statutory or external regulations and codes of good practice.
• Ensures appropriate leadership skills are present at every level through creating a motivational and supportive work environment in which employees are coached, trained and provided with career opportunities through development
• Allocates the different work to the respective employees considering experience, complexity, workload and organizational efficiency
• Continuously monitors and evaluates team workload and organizational efficiency with the support of IT systems, data and analysis and team feedback and makes appropriate changes to meet business needs.
• Provides team members/direct reports with clear direction and targets that are aligned with business needs and GIT objectives

KEY RELATIONSHIPS

• Global IT
• Respective business function (Finance, HR, Brand Marketing, Digital/Wholesale/Retail, etc.)
• Global Sales
• HR (Senior) Management
• Controlling

REQUISITE EDUCATION AND EXPERIENCE / MINIMUM QUALIFICATIONS

• Four-year college or university degree with focus on Business Administration or IT or related areas, or equivalent combination of education and experience
• Proficient spoken and written command of English
• At least 10 year experience in Data Science
• Proven, hands-on experience building and productionizing agentic AI systems (LLM agents) and integrating them into products or platforms
• Hands-on experience with agentic frameworks and patterns (e.g., LangChain/LangGraph/LlamaIndex; tool use, chaining, multi-agent orchestration, self-reflection)
• 7 years of experience in relevant area
• 5 years of experience in team management including professional
• International Experience - ideally working abroad and mobile in leadership roles for multiple years and has functional/market experience in projects with a local/global perspective
• Participated in a global project execution/ significant contribution to local/functional project
• Strong understanding & knowledge of regional and global market landscape and the respective customer 
• Managed critical elements and cross functional and regional projects