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Job description
An exciting opportunity for an experienced Statistics Manager / Associate Director to join a highly respected healthcare research consultancy in South Manchester (The position can be based in London too).
You'll be part of a specialist Advanced Analytics team, working at the forefront of applied statistics, AI integration and interactive tool development. This is a role for someone who thrives on complex problem-solving, enjoys pushing methodological boundaries, and wants to see their work directly influence strategic healthcare decisions.
If you're passionate about advanced modelling, commercial impact and building smart, efficient analytical solutions, this could be your next step.
Everything you need to know about the role
As Statistics Manager / Associate Director, you'll play a central role in designing, delivering and evolving advanced analytical approaches across a wide portfolio of healthcare research projects.
You will:
- Partner with research teams to shape study designs that enable robust, insightful analysis
- Lead the development, validation and refinement of advanced statistical models
- Apply a wide range of multivariate and advanced techniques including regression, conjoint/discrete choice, segmentation, pricing models, structural equation modelling and more
- Build and enhance simulation tools, dashboards and interactive applications (e.g. R-Shiny, Excel/VBA, Python, Power BI)
- Drive efficiencies through automation of data checking, model workflows and reporting outputs
- Contribute to the integration of AI into analytics processes to enhance value and innovation
- Act as a senior statistical voice in proposals and client discussions, clearly explaining complex outputs to non-technical audiences
- Lead analytic brainstorming sessions to solve complex or bespoke client challenges
- Develop internal best-practice standards, documentation and quality control frameworks
- Coach and mentor colleagues on statistical techniques, coding and model development
- Balance commercial awareness with analytical rigour, ensuring solutions are both methodologically sound and business-relevant
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Requirements
- A Master's or PhD (or equivalent applied experience) in statistics, mathematics, data science or a related discipline
- 6-8+ years' experience applying advanced statistical techniques in a commercial or research environment
- Strong expertise across multivariate methods including regression (linear, multinomial, ordinal), conjoint/discrete choice, segmentation and driver analysis
- Experience with modelling categorical and ordinal data (logit/log-linear approaches)
- Hands-on experience with data manipulation, weighting, significance testing and sample size calculations
- Experience building simulation models, war gaming tools or interactive dashboards
- Knowledge of advanced methods such as SEM, PLS-PM, Bayesian approaches, hierarchical models, latent class models, Hidden Markov Models, Monte Carlo methods or time-series forecasting
- Exposure to machine learning techniques (e.g. k-means, Gaussian mixtures, SVM), with neural networks or Kohonen maps as a bonus
- Advanced use of R, plus at least two of the following: Sawtooth (CBC/HB), SPSS, Python, SAS, Matlab, XLStat, GitHub
- Ability to combine survey data with secondary sources for validation and modelling
- Strong experimental design experience
Alongside technical depth, you'll be:
- A clear communicator who can translate complex outputs into meaningful business insight
- Comfortable juggling multiple deadlines in a fast-paced, client-driven environment
- Naturally collaborative and energised by team brainstorming
- Detail-focused, organised and commercially aware
- Confident leading discussions with both technical colleagues and senior client, * Exposure to innovative AI-enabled workflows
- A collaborative, intellectually curious team environment
- Real influence on strategic healthcare decisions
- Clear scope for leadership and continued technical development
Benefits & conditions
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