M09 - Data Scientist

Role Overview We are seeking a Data Scientist to support multiple product squads working with government agencies to redesign operational workflows and develop AI-enabled solutions.

The successful candidate will be responsible for analysing large operational datasets, identifying patterns and anomalies, and developing machine learning models to support risk assessment, decision-making, and workflow automation.

This is a hands-on role that involves end-to-end data science activities, including exploratory data analysis, feature engineering, model development, data pipeline implementation, and production deployment.

Key Responsibilities

Analyse large and complex operational datasets to identify patterns, anomalies, outliers, and potential risk indicators. Develop and implement machine learning techniques, including anomaly detection, clustering, segmentation, classification, and risk scoring.

Build and optimise supervised machine learning models using historical data and labelled datasets. Perform data preprocessing, cleaning, transformation, and feature engineering using structured and unstructured data.

Design and implement model evaluation frameworks, including precision, recall, false positives, false negatives, and other relevant performance metrics. Collaborate with business stakeholders and domain experts to translate operational challenges into data-driven solutions.

Design, develop, and maintain scalable data processing pipelines and feature engineering workflows. Develop production-ready machine learning models and scoring pipelines, integrating them with applications developed by engineering teams.

Monitor deployed models to ensure performance, data quality, reliability, and detection of data drift. Conduct exploratory data analysis to identify opportunities for process improvement, workflow redesign, and automation.

Explore and apply Large Language Models (LLMs) and other AI techniques alongside traditional statistical and machine learning approaches where