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Work Location - Sydney/ Melbourne
This role is required to maintain the lifecycle of models developed by the Data Science chapter and develop APIs/systems on top of these models. Machine Learning Engineer (MLE) will deploy models across various platforms (A2P/GME, and batch) as needed, manage end-to-end pipelines, logs, and address queries and issues.
What you’ll do
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Manage project progress, metadata collection, and data development with minimal supervision, ensuring timely and accurate delivery.
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Maintain and organize information within documentation repositories.
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Conduct investigations into internal and external stakeholder queries, operating under the guidance of the Team Leader.
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Analyze problems, identify root causes, and formulate clear findings and observations.
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Propose effective resolutions and communicate results to stakeholders, with moderate guidance.
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Maintain up-to-date knowledge of industry regulatory requirements, including reporting mandates and compliance standards.
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Provide support for internal and external inquiries related to data standards.
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Perform intermediate-level data quality checks, adhering to established procedures.
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Follow established security protocols to protect sensitive data.
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Identify and report potential security vulnerabilities.
What experience you need
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Bachelor's degree in STEM or related field (Master's preferred).
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2+ years of data engineering or related experience.
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Proficiency in Python, SQL, or scripting languages (intermediate level).
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Basic understanding of Google Cloud Platform (GCP) and cloud computing.
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Experience building and maintaining basic data pipelines.
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Experience supporting data model design and implementation.
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Proficient Git usage and contribution to team repositories.
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Cloud certification (strongly preferred)
What could set you apart
- GCP and extensive Python experience
- Interest in and experience in Data and Data Science, modelling, and AI
What’s in it for you?
At Equifax, we are on a mission to ensure that you have the support, resources and opportunities to Power Your Possible. Here are just a few ways we give back to our teams:
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Hybrid Work Model
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Additional Leave Allocations + Public Holiday Swaps
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Discounted Gym Memberships
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Discounted Private Health Cover (and discounted Pet Insurance if you want it!)
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Employee Stock Purchase Plan
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Career Development and Learning
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A Diverse and Inclusive Workplace and Environment
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Wellbeing Resources
Primary Location:
AUS-MelbourneAUS-Sydney-Blue-Street
Function:
Function - Data and Analytics
Schedule:
Full time
