Data Science Manager

Data Science Manager - Melbourne, Victoria, Australia A$100,000.00-A$120,000.00 Full-time, Mid-Senior level, Engineering and Information Technology, Business Consulting and Services 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. Key Responsibilities Consult with clients to explore and define business problems and advise on how to apply data analytics, business intelligence, and machine learning to solve them. Employ advanced analytics and statistical methods to prepare and analyze data for (predictive) modelling, from prototypes to production. Bring expertise in key areas such as customer intelligence (segmentation, behavior analysis, personalization, recommender systems, forecasting). Build comprehensive reporting and intelligence solutions for business users and management to leverage data-driven insights for decision making. Establish standards in statistical analysis, AI, machine learning, and data visualization to ensure consistency across projects and teams, and prepare reports and presentations for relevant stakeholders (client side & internal). Support business development activities in contributing to proposals and demonstrations. Must-Have Five 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). 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 (Databricks, Azure Synapse, AWS SageMaker, Google Cloud Vertex AI). Experience with data science, data visualization, and data analysis tools (scikit-learn, pandas, 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 data visualization tools (Tableau & Power BI), graphing and chart libraries (matplotlib, plotly). Experience working in a client-facing consulting role, having great written and verbal communication skills, and the ability to work closely with stakeholders. Flexibility and willingness to travel. Experience in agile methodologies and relevant tools (Confluence, Jira, git). Experience working in cross-cultural and cross-disciplinary teams. Nice-to-Have Understanding of data (management) platforms (CDP, CRM, DMP, Big Data Lakes, Cloud) and tools (ETL, Processing, marketing automation). Experience in production environments for Machine Learning products, knowledge of model deployment and lifecycle management tools (Docker, Kubernetes). Solid knowledge of software engineering principles & deployment methods (cloud environments). Experience in data-driven marketing, campaign development, measurement, and optimization, Martech, CDP. Industry experience in Finance, Automotive, Logistics, Energy, or public sector. Referrals increase your chances of interviewing at Publicis Sapient by 2x #J-18808-Ljbffr