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Senior Data Scientist

Posted on June 27, 2026 by Makereatu Technology Limited

  • Full Time

Senior Data Scientist

ABOUT MAKEREATU

Makereatu Technology Limited is a Dunedin-based AI company building governance assessment systems for infrastructure projects funded by commercial entities, governments, and multilateral development banks (MDBs). Our R&D programme combines machine learning, cognitive science methodology, and infrastructure governance analysis — producing both production AI systems and peer-reviewed research.

THE ROLE

Designing reliable AI systems for infrastructure governance requires more than engineering. Our assessment instruments — expert elicitation surveys, ML scoring models, and training datasets derived from expert judgement — must meet research standards: rigorously designed instruments, validated models, and publishable findings.

The Senior Data Scientist applies rigorous quantitative research methodology — developed through doctoral study and demonstrated by peer-reviewed publication — to the design and validation of these systems. The role requires the ability to design psychometrically valid expert elicitation instruments using multi-criteria decision analysis; develop training datasets using experimental protocols to research standard; and apply advanced predictive modelling to high-dimensional governance data. These methodological requirements draw directly from cognitive science and neuroscience research practice.

The role also requires familiarity with MDB project documentation — PADs, PCRs, EARRs, procurement documents, supervision reports — from ADB, World Bank, IFC and equivalent organisations.

WHAT YOU WILL DO

  • Design and administer expert elicitation instruments using MCDA methods — from instrument design and pre-testing through data collection, validation and analysis
  • Develop and curate training datasets for AI governance models — annotation, labelling, structuring and quality validation using experimental protocols to research standard
  • Apply Python and R predictive modelling (Random Forest, XGBoost, Elastic Net, SVR, PLS and ensemble methods) to high-dimensional governance datasets
  • Contribute to design and validation of quantitative governance assessment models using cognitive science and psychometric methodology
  • Engage with MDB project documentation — PADs, PCRs, EARRs, procurement documents and supervision reports — to inform model design and training data development
  • Develop and maintain specialised training data corpora including annotation schema design and inter-rater reliability testing
  • Contribute to peer-reviewed publication in data science, AI governance, cognitive science and infrastructure analytics
  • Maintain rigorous R&D documentation for RDTI compliance

WHAT YOU NEED

Qualifications:

  • Doctoral degree (PhD) in neuroscience, cognitive science, computational neuroscience, psychology, data science, computational biology, or closely related quantitative field with substantial ML component — minimum. Not substitutable by years of experience.
  • Minimum three peer-reviewed journal publications in data science, ML, neuroscience, cognitive science or related quantitative discipline

Research Methodology — Essential:

  • Experience designing and administering quantitative survey or elicitation instruments — design, pre-testing, piloting, data collection and psychometric validation
  • Experience applying experimental research protocols from design through analysis and documentation to publication standard
  • Ability to translate academic research methodology into operational data pipeline and model development tasks

Technical Skills — Essential:

  • Advanced Python and R for data processing, statistical analysis, ML and reproducible research workflows
  • Demonstrated experience: Random Forest, XGBoost, Elastic Net, SVR, PLS Regression and multistage cross-validation
  • Experience with large-scale multidimensional datasets — population health, neuroimaging, biomedical or equivalent

MDB Knowledge — Essential:

  • Familiarity with MDB infrastructure project processes and documentation (ADB, World Bank, IFC or equivalent), or demonstrated ability to rapidly acquire domain-specific knowledge in complex governance environments

WHAT WOULD MAKE YOU STAND OUT

  • Experience with UK Biobank or equivalent large-scale longitudinal dataset
  • Publications in Nature family, PLOS, eLife, Frontiers, Cerebral Cortex or equivalent
  • Familiarity with MCDA methodologies (AHP, conjoint analysis or equivalent) * Experience in interdisciplinary research bridging domain experts, clinicians and data scientists

WORKING CONDITIONS

  • On-site only — Corstorphine, Dunedin. No remote work.
  • Must be Dunedin-based or able to relocate immediately upon appointment * Permanent, full-time (40 hours/week, Monday to Friday) * NZD $45/hr (approx. $93,600/yr)

Pay: $45.00 per hour

Ability to commute/relocate:

  • Dunedin, Otago: Reliably commute or planning to relocate before starting work (Required)

Application Question(s):

  • MDB and Infrastructure Domain Knowledge?
  • Minimum three peer-reviewed journal publications in data science, ML, neuroscience, cognitive science or related quantitative discipline?

Education:

  • Doctoral Degree (Required)

Licence/Certification:

  • Do you have a valid Driver Licence (Required)

Location:

  • Dunedin, Otago (Required)

Work Location: In person


Advertised until:
July 27, 2026


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