Transformation Director (Data Science)

Overview

In this role you lead a multi-workstream data science transformation, ensuring delivery hygiene and coherent governance for senior leadership visibility. You shape business cases, align stakeholders, and govern progress, risks, and benefits to maximise business impact. You will apply data science and ML understanding to challenge plans and ensure technical accuracy in reporting. This position sits at the forefront of Elsevier’s mission to advance science and improve health outcomes by transforming how data and analytics drive decisions.

Pay / Benefits

• flexible working
• private medical benefits
• pension scheme
• wellbeing programs
• life assurance
• generous holiday allowance

Responsibilities

• Define and improve standards for programme and project management across the transformation, including planning, risk and benefits tracking
• Assess and close hygiene gaps across workstreams; coach leads to timely remediation
• Provide independent delivery assurance and flag early risks
• Apply technical understanding of data science, ML, AI engineering to challenge plans and risk assessments
• Run governance cadence and produce executive-facing packs, dashboards, and narratives
• Establish a single source of truth for status, milestones, risks, and benefits with high data quality
• Maintain a coherent view of the change portfolio and identify overlaps, conflicts and gaps
• Support prioritisation, sequencing, and alignment with Data Science OKRs
• Help build robust business cases with problem statements, options, costs, benefits, and risks
• Collaborate with Finance to validate assumptions and track realised benefits
• Shape the pipeline of future initiatives to fit the portfolio and strategy

Key requirements

• A data science, ML or AI engineering background with hands-on or governance experience
• Extensive experience running portfolio or transformation governance in a complex technical setting
• Proven ability to present reporting to senior/executive audiences with credibility
• Strong programme management methods (MSP, PRINCE2, P3O, Agile/SAFe) used pragmatically
• Experience building or contributing to business cases including benefits and financial modelling
• Sharp analytical and written communication skills; ability to simplify complexity
• Confident challenger who can influence without formal authority

• stakeholder management
• clear written and verbal communication
• influencing without authority
• Data science, ML or AI engineering background
• Governing data science delivery and technical content for non-technical audiences
• Experience with benefits tracking and financial modelling

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