Description

The Senior Data Scientist will own the statistical performance of commercially released machine‑learning models, handling training, validation, issue identification, and improvement through retraining, labeling, and sampling, while collaborating with Machine Learning Engineers who build the underlying tooling and pipelines.

• Lead a coherent program of data science projects focused on modelling.
• Supervise and support other data scientists on modelling initiatives.
• Provide technical leadership, fostering learning, professional development, collaboration, and business value.

Requirements

• Own statistical performance of commercially released models, including training, validation, issue identification, retraining, labeling, and sampling.
• Required: postgraduate qualification (Masters/PhD) in data science or equivalent knowledge.
• Required: end‑to‑end data science project delivery experience aligned with business goals.
• Required: strong scientific Python coding in Linux with Git version control.
• Required: solid grasp of machine learning fundamentals such as regularisation, hyperparameter optimisation, and validation methods.
• Required: scientific rigor in hypothesis formulation and statistical testing.
• Desirable: experience with computer vision and geospatial data in machine learning.
• Desirable: software engineering skills for contributing production‑quality code to shared codebases.
• Desirable: cloud computing experience (AWS or GCP) using distributed virtual machines and containerisation.
• Desirable: deep learning expertise applying modern neural networks to ML problems.
• Desirable: experience working at scale with large datasets requiring distributed computing.

Benefits

The role offers a flexible hybrid environment that values fast, smart work, inclusive culture, and personal well‑being, allowing teams to choose when in‑person collaboration adds the most value without mandatory office days.

Additional information includes resources on Nearmap AI, a note that recruitment agencies are not accepted, and a comprehensive benefits package supporting emotional, physical, and financial wellness.

• Benefit: Quarterly wellbeing "YOU" day off – four additional days annually.
• Benefit: Access to LinkedIn Learning.
• Benefit: Wellbeing and technology allowance.
• Benefit: Annual flu vaccinations.
• Benefit: Hybrid flexibility and Work‑from‑Anywhere policy for up to 4 weeks per year.
• Benefit: Nearmap subscription, stocked kitchen, catered lunches, and showers.
• Benefit: Flexible hybrid approach with no mandatory office days.

Training + Development

Interview process

Visa Sponsorship

Security clearance