In-Demand Analytics engineer data & analytics Jobs in Melbourne Vic

Data Scientist
Publicis Groupe Holdings B.V —Southbank VIC
- Azure
- Data analysis skills
- SQL
Quick Apply
6h
Lakebase Specialist Sales
Databricks —Melbourne VIC
- Azure
- Sales
- Databases
Principal Mining Engineer (Underground)
AMC Consultants —Melbourne VIC
- Full-time
- Hybrid work
- Business development
- Bachelor's degree
- Communication skills
- Life insurance
Quick Apply
Senior / Principal Mining Consultant (Strategy Optimization)
AMC Consultants —Melbourne VIC
- Full-time
- Hybrid work
- Doctoral degree
- Master's degree
- Analysis skills
- Life insurance
Quick Apply
Data Centre Security Manager , Data Centre Security
Amazon Corporate Services Pty Ltd —Melbourne VIC
- Full-time
- AWS
- Negotiation
- Analytics
- Health insurance
- Employee assistance program
Staff Data Engineer (Data Architect) - Sydney/Melbourne
Xero —Hawthorn VIC
- Full-time
- Hybrid work
- APIs
- AI
3h

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Lakebase Specialist Sales
Databricks —Melbourne VIC
Enable the field by sharing Lakebase best practices, success stories, and sales motions with broader sales teams, helping scale Lakebase proficiency across the…

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Data Scientist

Publicis Groupe Holdings B.V -
Southbank VIC

Quick Apply

Job Details

6 hours ago

Qualifications

Jira
Power BI
Azure
Deployment
NumPy
Data analysis skills
Logistics
Git
Tableau
SQL
AWS
Docker
Machine learning
Confluence
REST
Forecasting
Agile
JSON
Systems analysis
Business requirements
AI
Communication skills
Marketing

Full Job Description

At Publicis Sapient, We’re Building Something Truly Exceptional! Our Data & AI practice designed to redefine how businesses operate, grow, and deliver value. We're not talking about trendy buzzwords—we're talking about real impact. AI is transforming industries, enriching customer experiences, and unlocking untapped potential—and we're leading that change every day

Join Publicis Sapient as a Senior Associate, Data Science and help shape the future of data-driven digital transformation. In this role, you will help to drive the Data & AI practice by playing a critical role in delivering solutions for our clients and contributing to business development activities. This is a hands-on role where you will apply advanced techniques for data analytics, machine learning, and AI as a core building block for our services.

You will leverage your experience across industries to understand business requirements, identify approaches and designs, and work with multi-disciplinary teams to develop solutions. As an evangelist for Analytics, you will engage with broader data, engineering, product, and strategy practices to provide insights into best practices and emerging technologies and techniques, ensuring that the solutions we develop are data and insight driven.

What you will do:

Design and implement advanced analytical solutions and machine learning models that drive measurable business value, selecting appropriate methodologies based on problem context, ensuring models are robust and interpretable, to ensure solutions meet client needs, not just basic requirements.
Build client relationships and deliver end-to-end data science engagements, from problem framing and exploratory analysis through to model deployment and impact measurement, translating complex analytical findings into actionable business recommendations and managing stakeholder expectations throughout the project lifecycle.
Thrive in cross-functional team environments, working closely with data engineers, analysts, software engineers, experience and strategy specialists, and business stakeholders to deliver integrated solutions, facilitating effective communication across technical and non-technical audiences, and driving consensus on complex decisions.
Help shape and grow our Data practice, invest in continuous learning and support development of others, stay current with emerging technologies and methodologies, and contribute to a collaborative team culture where knowledge sharing and growth are valued. Establish standards to ensure consistency across projects and teams.
Contribute to business development and firm visibility by participating in proposal development and client pitches, creating thought leadership content through, engaging with the broader data engineering community, and identifying opportunities to expand existing client relationships.

Experience and Skills required:

8+ years of relevant professional experience working as a data scientist.
A passion for using AI and data for business transformation and a thirst to continually learn and keep pace with the latest innovations and applications.
Experience in statistical methods and modelling techniques (e.g., Random Forests, Clustering, Linear Regression) and expertise in key areas such as customer intelligence (segmentation, behavior analysis, personalization, recommender systems, forecasting).
Experience using and integrating generative AI models and platforms, agentic solutions, and context engineering techniques.
Experience with programming languages (Python, R, SQL) and AI/ML platforms (e.g. Databricks, and cloud platforms (e.g. Azure Synapse, AWS SageMaker, Google Cloud Vertex AI).
Experience with data science, data visualization, and data analysis tools (e.g., scikit-learn, pandas and NumPy, Apache Spark, matplotlib, ggplot2).
Experience working with large volume data sets and multiple data formats and interfaces (SQL, JSON, REST, Parquet, streaming, geospatial, unstructured).
Technical knowledge of reporting and data visualization tools (Tableau & Power BI), graphing and chart libraries (e.g., matplotlib, plotly).
Experience working in a client-facing (ideally) consulting role, having great written and verbal communication skills, and the ability to work closely with stakeholders, or having been part of a project team.
Flexibility and the willingness to travel are required for this role, as you might need to spend time on-site with our clients.
Experience in agile methodologies and relevant tools (Confluence, Jira, git).
Experience working in cross-cultural and cross-disciplinary teams.

Desired Qualifications

Understanding of data (management) platforms (CDP, CRM, DMP, Big Data Lakes, Cloud) and tools (ETL, Processing, marketing automation, etc.).
Experience in production environments for Machine Learning products, knowledge of the tools that are needed for model deployment and lifecycle management in ML engineering (Docker, Kubernetes).
Solid knowledge of software engineering principles & deployment methods (preferably in cloud environments). Experience in data-driven marketing, campaign development, measurement, and optimization, Martech, CDP, etc.
Industry experience in the Finance, Automotive, Logistics, Energy, or public sector.

Quick Apply

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analytics engineer data & analytics jobs in melbourne vic

Data Scientist

Lakebase Specialist Sales

Principal Mining Engineer (Underground)

Senior / Principal Mining Consultant (Strategy Optimization)

Data Centre Security Manager , Data Centre Security

Staff Data Engineer (Data Architect) - Sydney/Melbourne

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