Machine Learning Engineer

Job Responsibilities

Develop and refine analytical and machine learning use cases in collaboration with internal business stakeholders, aligned with Analytics Leads and strategic partners.
Play an active role in analytics and data science projects of varying scope, priority, and urgency within the insurance domain.
Translate complex business requirements into analytical and machine learning solutions, and effectively bridge business and technical discussions.
Explore, interrogate, and interpret large datasets and machine learning models to rapidly formulate, test, and refine hypotheses.
Integrate, analyse, and present insights using clear data visualisations and concise storytelling to communicate findings and recommendations to business users.
Act as a Machine Learning subject matter expert, supporting Data & Analytics colleagues and business stakeholders.
Provide direction and oversight to onshore and offshore analytics and data science initiatives.
Plan and manage own work during sprint cycles, including accurate estimation of effort for tasks and user stories.
Ensure adherence to company policies, procedures, and relevant regulatory or legislative requirements.
Share knowledge and contribute to reusable frameworks, best practices, and analytical techniques across teams.

Proven experience in generating actionable insights from large and complex datasets.
Strong proficiency in Python and SQL.
Solid knowledge of computer vision, particularly applications involving Azure Document Intelligence.
Good understanding of DevOps and MLOps practices for model deployment and lifecycle management.
Experience with Azure Databricks is an added advantage.
Demonstrated experience working on collaborative programming projects.
Comfortable working in a Linux-based environment.
Bachelor's to Postgraduate degree in a quantitative discipline such as Computer Science, Engineering, Statistics, Mathematics, or a related field, or an equivalent combination of education and relevant work experience.