Ingeus
Quantitative Analyst
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Job Description
The Quantitative Analyst transforms complex clinical data into actionable intelligence that supports clinical governance, service improvement, project prioritisation and strategic decision-making across HAAS.
The postholder uses statistical analysis, trend monitoring, risk stratification and predictive techniques to identify emerging patterns, early warning signs and opportunities for intervention. They will translate analysis into clear recommendations for Clinical Excellence and senior stakeholders, enabling the service to move from retrospective reporting towards proactive, evidence-led management.
The role liaises primarily with Clinical Excellence and in partnership with Clinical Operations, Data and Insights, Learning & Development, and other relevant functions. It provides analytical support to clinical projects, evaluates the impact of interventions and strengthens the evidence base for future service design.
Qualifications
Essential qualifications and experience
- Degree or equivalent professional experience in data analytics, statistics, mathematics, health informatics, public health, operational research or a related discipline.
- Substantial experience in an analytical, business intelligence, healthcare analytics or comparable evidence-led role.
- Demonstrable experience analysing complex datasets and translating findings into practical recommendations.
- Experience designing dashboards, scorecards and reports for senior decision-makers.
- Experience supporting projects or improvement activity through baseline analysis, evaluation and benefits measurement.
- Experience working with sensitive or regulated data and applying strong information governance controls.
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Essential technical capability and behaviours
- Advanced Excel and strong proficiency in Power BI or an equivalent visualisation platform.
- Practical SQL capability and experience preparing, joining and validating data from multiple sources.
- Competence in statistical analysis, including selection and explanation of appropriate methods.
- Ability to create clear, reproducible analytical outputs and maintain robust documentation.
- Excellent written, verbal and visual communication skills, with the ability to explain technical findings to non-technical audiences.
- Selects proportionate methods, challenges assumptions and avoids overstating what the data can prove.
- Connects analysis to quality, safety, fairness, practitioner practice and customer experience.
- Turns complex findings into a clear narrative, decision points and practical recommendations.
- Investigates unexpected variation and seeks the underlying drivers rather than accepting headline measures.
- Works effectively across clinical, operational and technical disciplines while maintaining analytical independence.
- Plans work, manages priorities and produces accurate outputs to agreed standards and timescales.
- Uses data ethically, protects sensitive information and is transparent about quality and limitations.
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Desirable criteria
- Experience within healthcare, health assessment, disability services, the NHS, public services or another regulated environment.
- Experience using Python, R or another statistical programming language.
- Knowledge of clinical governance, quality assurance, risk management or continuous improvement methodologies.
- Experience of predictive analytics, control charts, natural language analysis or machine-learning methods.
- Understanding of benefits realisation, service evaluation and evidence-based decision-making.
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