LMG is the largest aggregator across Australia and New Zealand supporting a community of over 7000 brokers and advisers.
Proudly family-owned and led, LMG supports businesses operating under their own brand or the Loan Market brand, and partners with over 70 banks and lenders.
The business has grown rapidly, reaching a $370 billion loan book and helping more than 300,000 customers in 2023.
We're not a conventional company with a lot of rules and hierarchy, and we don't intend to become one.
We're a big company with a start-up attitude.
Our success is based on hiring outstanding people and accepting nothing less than being the best at what we do.
About the role:
As a Data Scientist in the Data & Analytics team, you will be responsible for developing data driven, AI and ML solutions to deliver value to the organisation.
You will work with business stakeholders, data engineers, data modellers, software engineers and analysts in cross functional teams to deliver end-to-end outcomes.
You will also get opportunities to build proof of concepts to determine the value of AI/ML solutions to push the boundaries to create value for our brokers and their clients.
This is a hybrid role (2 days in the office per week) that can be done from Sydney, Melbourne or Brisbane
Key Responsibilities: Design, develop, and implement AI and machine learning solutions tailored to solve problems in a practical and timely manner.
Evaluate the performance, stability, and scalability of developed models, ensuring they meet the necessary business requirements and standards.
Partner with data engineering teams to deploy models on Google Cloud Platform (GCP) and ensure seamless integration into existing workflows.
Leverage dbt (Data Build Tool) to create reusable features for the data and analytics community.
Monitor model performance and maintain optimization, stability, and accuracy over time.
Stay abreast of industry trends, advancements, and innovations in AI, machine learning, and data science, driving continuous improvement and innovation within the team.
Communicate technical insights and recommendations clearly and effectively to both technical and non-technical stakeholders.
To succeed in this role you will bring with you: Bachelor's degree in Data Science, Statistics, Computer Science, or a related quantitative field.
2+ years of hands-on experience in data science, including model development and deployment.
Proficiency in Python and SQL for data manipulation and machine learning model development.
Problem-solving skills and the ability to translate business problems into data science solutions.
Good communication skills with the ability to present findings and technical solutions to diverse audiences.
Familiarity with GCP and its services (BigQuery, Vertex AI etc.
), and dbt is a plus.
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