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Open nowPosted 69 days ago

Data Scientist

Publicis Groupe Holdings B.V3,068 open roles

Where
Melbourne, Victoria, Australia
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Your applicationOpen nowData ScientistPublicis Groupe Holdings B.V · Melbourne, Victoria, Australia
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Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. Publicis Groupe Holdings B.V postings stay open a median of 2 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: posted 69 days ago

Publicis Groupe Holdings B.V median: 2 days open

The posting

Company description Publicis Sapient is a digital transformation partner helping established organizations get to their future, digitally enabled state, both in the way they work and the way they serve their customers. We help unlock value through a start-up mindset and modern methods, fusing strategy, consulting, and customer experience with agile engineering and problem-solving creativity. United by our core values and our purpose of helping people thrive in the brave pursuit of next, our 20,000+ people in 53 offices around the world combine experience across technology, data sciences, consulting, and customer obsession to accelerate our clients’ businesses through designing the products and services their customers truly value. Overview 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. Additional information An inclusive workplace that promotes diversity and collaboration. Access to ongoing learning and development opportunities. Competitive compensation and benefits package. Flexibility to support work-life balance. Generous paid leave and holidays. Wellness program and employee assistance. As part of our dedication to an inclusive and diverse workforce, Publicis Sapient is committed to Equal Employment Opportunity without regard for race, color, national origin, ethnicity, gender, protected veteran status, disability, sexual orientation, gender identity, or religion. We are also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, you may contact us at [email protected]

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