As an Advanced Analytics Specialist / Expert, you are responsible for designing, executing and interpreting advanced statistical analysis and marketing science outputs that help clients make better business decisions. The pillar covers methods such as conjoint and choice modelling, MaxDiff, pricing analytics, clustering and segmentation, driver analysis, regression, predictive modelling and other advanced quantitative techniques.
You support project delivery by translating business questions into fit-for-purpose analytical approaches, preparing or specifying analysis plans, executing robust modelling, validating outputs, and turning statistical results into clear implications, scenarios and recommendations. A core part of the role is sense making: connecting advanced outputs to the wider research story so that findings are understandable, commercially relevant and usable by client teams.
The role is expected to be confident in core advanced analytics and marketing science tools, including Sawtooth, R, SPSS, Python, Excel and relevant Human8 tools, while acting as a technical sparring partner for Client Service Teams, Project Delivery Managers, Data Processing specialists and senior experts on analytical feasibility, methodological quality and interpretation of results.
Advanced Statistical Analysis & Modelling
- Translate client and research questions into appropriate advanced analytical approaches, including conjoint/CBC, MaxDiff, pricing analytics, clustering, segmentation, driver analysis, regression and predictive modelling.
- Execute statistical modelling and marketing science analysis using robust, documented and quality-controlled methods.
- Validate model inputs, assumptions, outputs and diagnostics to ensure analytical conclusions are reliable and fit for purpose.
- Develop simulators, analytical outputs, scenario tools, models, reports or other deliverables that help project teams and clients understand choices, trade-offs and drivers of behaviour.
Sense Making, Interpretation & Client Impact
- Interpret statistical outputs and translate them into clear, commercially relevant insights, implications and recommendations.
- Connect advanced analytics findings with broader research evidence, stakeholder context and the overall client story.
- Explain complex methods and outputs in accessible language for internal teams and external clients.
- Guide teams on how to use advanced outputs appropriately, including limitations, interpretation boundaries and decision-making implications.
- Provide a clear point of view on what the numbers mean and what actions they suggest.
Method Management, Guidance & Continuous Improvement
- Develop and improve analytical frameworks, templates, syntax, simulators, documentation and quality checks for recurring marketing science methods.
- Provide technical guidance to colleagues on method selection, analysis setup, interpretation and troubleshooting.
- Stay current with relevant marketing science, statistical and data science methods, identifying opportunities to apply new thinking responsibly.
- Contribute to knowledge sharing, training and capability building across the Advanced Analytics community.
- Support governance around methodological standards, reproducibility, model quality and appropriate use of advanced outputs.
Tools & Platforms
- Use advanced analytics tools such as Sawtooth, R, SPSS, Python and Excel to design, run, validate and interpret statistical and marketing science analyses.
- Use Copilot and other approved productivity tools responsibly to support efficiency, documentation, checking and workflow improvement.
- Use relevant Human8 tools and methods to support analysis preparation, output review, visualization, synthesis and storytelling where applicable.
- Bachelor’s or Master’s degree in Statistics, Data Sciences, Economics, Operations Research, Applied Mathematics, Computer Science, or related field of study is desirable
- 3-4 years of relevant experience
Success Measures / KPIs
- Accuracy, robustness and relevance of advanced statistical analysis and marketing science outputs
- Quality of analysis plans, model validation, documentation and reproducibility
- Ability to translate complex outputs into clear insights, implications and recommendations
- Timeliness and usability of deliverables such as models, simulators, analytical reports and scenario outputs
- Effective use of required tools, including Sawtooth, R, SPSS, Python, Excel, Copilot and relevant Human8 tools
- Contribution to method improvement, training, documentation, quality standards and capability building
