Senior Data Scientist
Employment Info
JOB DETAILS
Requirements
- Have strong foundations in statistical modelling, machine learning, Generative AI, and applied data science.
- Are confident using Python or R, SQL, and modern data science workflows to work with large and complex datasets.
- Have experience designing and delivering cloud-based data science, ML or GenAI solutions using AWS services, with an understanding of scalable architecture, security, governance and production deployment considerations.
- Can build robust, reusable, and well-documented data pipelines and analytical assets.
- Understand the importance of responsible AI, privacy, explainability, and ethical use of people data.
- Can translate ambiguous business questions into clear analytical approaches and practical solutions.
- Are strong storytellers who can communicate complex findings to HR leaders, executives, and non-technical audiences.
- Have experience with BI and visualisation tools such as Tableau or Power BI.
- Bring curiosity about the future of work, skills, workforce transformation, and the role of AI in shaping employee experiences.
- Are self-motivated, experimental, collaborative, and comfortable working in ambiguity.
Responsibilities
- Partner with HR, business leaders, and Centres of Excellence to identify workforce challenges and translate them into high-value analytical, ML, and GenAI opportunities.
- Develop data science and AI solutions that support future workforce priorities, including skills, capability, workforce planning, employee experience, mobility, productivity, and organisational effectiveness.
- Build, evaluate, and deploy GenAI/ML models using appropriate statistical methods, performance metrics, and responsible AI practices.
- Identify opportunities to embed AI and advanced analytics into HR processes, decision-making, and self-service insight experiences.
- Analyse large and complex workforce datasets, applying robust data preparation, feature engineering, modelling, validation, and interpretation techniques.
- Translate complex analytical outputs into clear narratives, dashboards, recommendations, and executive-ready insights.
- Collaborate with data engineers, platform teams, risk, privacy, andMLOpsteams to ensure solutions are scalable, secure, well-governed, and fit for production.
- Apply ethical, privacy-aware, and explainable AI practices when working with sensitive people data.
- Contribute to reusable analytical assets, frameworks, coding standards, and knowledge-sharing across the People Analytics Chapter.
- Coach and mentor team members, helping uplift data science, GenAI, and AI literacy across the chapter.
Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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