Principal Data Science Engineer

Job description

Job Purpose • Drive identification, prioritisation, and delivery of high-impact analytics and AI use cases across GSC Performance. • Translate complex business challenges into scalable, reusable analytics solutions and ensure integration into business processes. • Act as a trusted advisor to shape AI demand, guide stakeholders, and ensure measurable business value, adoption, and continuous improvement aligned with enterprise AI strategy and responsible AI principles. Key Responsibilities 1. Portfolio Shaping, Business Advisory & Use Case Prioritisation • Shape, triage, and prioritise AI/analytics demand across the GSC, identifying synergies, reuse opportunities, and when simpler solutions are more appropriate • Act as a trusted advisor to frame use cases, define problem statements, value hypotheses, and adoption success criteria 2. Advanced Analytics & AI Solution Development • Lead the design and delivery of advanced analytics and AI solutions (predictive, optimisation, ML/GenAI), aligned to business needs • Ensure solutions are scalable, reusable, and aligned to enterprise architecture, standards, and guardrails 3. End-to-End Model Lifecycle & Operationalisation • Oversee the full lifecycle of analytics solutions, from data sourcing and modelling, training and testing, to deployment and monitoring • Ensure models are robust, explainable, and production-ready, working with engineering/platform teams for operationalisation 4. Stakeholder Engagement & Decision Enablement • Partner with business, product, and engineering teams to identify opportunities and drive adoption of analytics solutions • Translate complex insights into clear, actionable recommendations to influence decision-making 5. Governance, Data Quality & Responsible AI • Ensure adherence to data governance, security, privacy, and compliance standards across all solutions • Establish model governance practices and promote responsible, ethical, and transparent use of AI 6. Cross-Functional Collaboration & Integration • Collaborate with Product, Engineering, and Platform teams to enable seamless integration and deployment of solutions • Embed analytics outputs into business workflows and ensure alignment with enterprise data & AI strategy 7. Thought Leadership & Technical Guidance • Provide guidance on appropriate analytics and AI approaches (ML, GenAI, advanced analytics), including feasibility and scalability • Stay abreast of emerging trends and drive adoption of new methodologies and best practices 8. Value Realisation & Continuous Improvement • Define and track value (business impact, productivity, adoption) to support evidence-based prioritisation • Drive continuous improvement through feedback, learnings from delivered use cases, and evolving business needs Basic Qualifications: Education: Master’s degree in AI or related field. Experience • 10 to 12 years of total experience, with strong relevance in data science / advanced analytics. • Proven experience delivering advanced analytics or data science solutions in a business environment. • Hands-on experience in statistical methods, machine learning, and advanced analytics techniques. • Experience working with enterprise data and complex datasets. • Exposure to supply chain / operations / performance measurement environments (preferred). Key Technical Competencies and Skills: • Advanced analytics, machine learning, and GenAI expertise • Strong problem framing and business translation skills • End-to-end model lifecycle management. • Data governance, security, and responsible AI understanding. • Stakeholder engagement and influencing skills. • Cross-functional collaboration (product, engineering, platform teams • Ability to translate insights into actionable business recommendations • Awareness of emerging AI/analytics trends and best practices. Skills Artificial Intelligence (AI), Business Analysis, Customer-Focused, Data Integrity, Digital Fluency, Financial Acumen, GxP Regulations, Lean Management, Problem Solving, Product Knowledge, Risk Awareness, Statistical Analysis, Strategic Alignment, Supply Chain Operations    Why GSK? Uniting science, technology and talent to get ahead of disease together. GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases – to impact health at scale. People and patients around the world count on the medicines and vaccines we make, so we’re committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.</