Data & Analytics Translator

Il y a 3 jours

Brussel Hoofdstad, Belgique E-Resourcing Belgium BV Temps plein 60 000 € - 90 000 €/an

We are looking for a Data & Analytics Translator to join our Data & Analytics team. This role is central to creating value from business-driven data and analytics initiatives. You will support the business and other stakeholders in their data-driven objectives across all stages: in the inspiration phase, helping identify the right use cases and prioritise them based on feasibility and value; in the ideation and prototyping phase, helping develop a minimum viable product and business case; and during implementation, ensuring the service or product is adopted by employees, embedded in the workflow, and measured for impact.

You will uncover and translate business requirements and needs in such a way that technical specialists in the D&A team can understand. This requires an understanding of both business objectives, goals and domain expertise, as well as D&A concepts, methods and techniques. It also requires strong soft skills with a focus on communication. You may also work with C-level executives and board members to support their data-driven vision, strategy and operating models.

Key Responsibilities

  • Identify, qualify and prioritise high-value AI, data and automation use cases.
  • Facilitate ideation, onboarding and solutioning workshops with business stakeholders.
  • Translate business challenges into clear AI, analytics and data requirements for technical teams.
  • Develop initial business cases, value assessments, KPIs and success criteria.
  • Coordinate use cases through the prototyping lifecycle, aligning business and technical teams.
  • Create executive-ready presentations, recommendations and decision materials.
  • Drive stakeholder engagement, adoption and change management activities.
  • Support handover to implementation teams and ensure solutions are embedded into business processes.
  • Track adoption, measure realised business value and identify opportunities for continuous improvement.

Required Skill Sets

  • Communication – conveying information to diverse audiences in a way that is easily understood and actionable.
  • Facilitation – hosting sessions to elicit ideas from others, understand their issues and encourage group participation.
  • Creative thinking – framing new concepts that spur use case ideation for business participants and brainstorming with business users about future products and services.
  • Teamwork – working with both business domain teams as well as D&A teams and IT staff.
  • Collaboration – fostering group problem solving and solution creation with business and technical team members.
  • Relationship management – creating relationships and building trust with internal and external stakeholders quickly.
  • Storytelling – creating a consistent storyline for better understanding and raising literacy.
  • Influencing – asserting ideas and persuading others to gain support across an organisation or to adopt new behaviours.
  • Presentation – comfort with public speaking and the ability to creatively and concisely express ideas to business and technical audiences.
  • Strong communication and stakeholder management.
  • Workshop facilitation and requirements elicitation.
  • Influencing and change management.
  • Collaboration across business and technical teams.
  • Creative problem solving and design thinking.
  • Ability to operate comfortably with senior leadership and executives.

Data & Analytics Skills

  • Analytics – diagnostic, descriptive, predictive and prescriptive.
  • AI – graph analysis, machine learning, natural language processing.
  • Data management – data integration (ETL) or metadata.
  • Data architecture – the difference between data warehouse, data lake or data hub.
  • Data structures – structured, semi-structured and unstructured data.
  • Data governance – MDM, data quality and data stewardship practices.
  • Statistical skills – understanding the difference between correlation and causation.
  • AI, analytics and data science fundamentals.
  • Data management, governance and architecture concepts.
  • Understanding of data products, data quality and data flows.
  • Statistical literacy and analytical thinking.
  • Programming languages: Python (R, SQL).
  • Business Intelligence tools, e.g. Microsoft Power BI.

Domain Skills

  • Business Acumen – understanding business concepts, practices and business domain language to engage in problem solving sessions and discuss business issues in stakeholder language.
  • Business Process Transformation – ability to understand how D&A can help redesign the way work is done.
  • Business data – th