Primary Details

Time Type: Full time

Worker Type: Employee

The purpose of this role is to apply scientific principles and data-driven analytics to improve the quality and performance of business units. This involves translating stakeholders' needs into analytically tractable problems, applying scientific methods and big data tools to resolve them, and communicating findings back to business owners. The role also includes taking ownership of technical project delivery and serving as a modelling and data science partner for assigned business areas to ensure scientific integrity in work products.

Responsibilities:

• Develop and refine analytical use cases with internal business customers in alignment with Analytics leads and partners.
• Play an active role in projects of diverse scope, range, priority and urgency within the insurance domain.
• Translate between business and analytical problems.
• Interrogate and interpret data and models to formulate, evaluate and iterate hypotheses quickly.
• Integrate, format and present relevant analyses and data visualizations to communicate results, findings and recommendations to business users.
• Act as a Machine Learning expert in order to support Data & Analytics colleagues and business stakeholders
• Direct the work of onshore and offshore analytics and data science projects.
• Plan own activities for each sprint, accurately estimating effort for stories/tasks.
• Ensure compliance with QBE policies and procedures and relevant legislation.
• Share knowledge and contribute reusable practices and techniques within and beyond the team.

Work Experience:

Necessary Work Experience includes:

• Some relevant work experience.

Preferred Work Experience includes:

• Experience in producing insights from large datasets.
• Analytics experience with R, Python, Spark.
• Collaborative programming project experience.
• Comfortable in a Linux environment.

Qualifications:

Necessary Qualifications include:

• Tertiary Degree or equivalent combination of education and work experience.
  

Preferred Qualifications include:

• Bachelor to Postgraduate Degree in a Quantitative field such as Computer Science, Engineering, Statistics, Mathematics or related disciplines.

Global Disclaimer:

The duties listed in this job description do not limit the assignment of work. They are not to be construed as a complete list of the duties normally to be performed in the position or those occasionally assigned outside an employee’s normal duties. Our Group Code of Ethics and Conduct addresses the responsibilities we all have at QBE to our company, to each other and to our customers, suppliers, communities and governments. It provides clear guidance to help us to make good judgement calls.

US Only Disclaimer:

To successfully perform this job, the individual must be able to perform each essential job responsibility satisfactorily. Reasonable accommodations may be made to enable an individual with disabilities to perform the essential job responsibilities.

US Only - Travel Frequency:

Infrequent (approximately 1-4 trips annually)

US Only - Physical Demands:

General office jobs: Work is generally performed in an office environment in which there is not substantial exposure to adverse environmental conditions. Must have the ability to remain in a stationary position for extended periods of time. Must be able to operate basic office equipment including telephone, headset and computer. Incumbent must be able to lift basic office equipment up to 20 lbs.

Skills:

Collaboration Tools, Communication, Critical Thinking, Data Analysis, Data Science, Data Visualization, Economics, Intentional collaboration, Machine Learning (ML), Managing performance, Process Improvements, Reporting and Analysis, R Programming, Sourcing Analytics, Stakeholder Management

How to Apply:

To submit your application, click "Apply" and follow the step by step process.

Equal Employment Opportunity:

QBE is an equal opportunity employer and is required to comply with equal employment opportunity legislation in each jurisdiction it operates.