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Cognizant Consulting is more than Cognizant’s consulting practice—we’re a global community of experts dedicated to helping clients reimagine their business. By combining deep industry expertise with leading technology and advisory capabilities, we deliver innovative solutions for Fortune 500 clients worldwide. And now, we’re looking for our next colleague to help shape the future of data, AI, and intelligent decision‑making.
About The Role
As a Senior Data Scientist, you will make an impact by designing, building, and deploying advanced machine learning and generative AI solutions that solve complex business challenges. You will be a valued member of our Technology Consulting - Data & AI team and work closely with clients, data engineers, cloud architects, and generative AI specialists across global engagements.
In This Role, You Will
- Design, develop, and optimize machine learning and AI models to address real‑world business problems across industries
- Lead data exploration, feature engineering, model training, validation, and performance evaluation aligned to business objectives
- Build and operationalize scalable ML pipelines using cloud‑native platforms and MLOps best practices
- Collaborate with generative AI engineers to integrate ML models with LLM‑based solutions, including retrieval‑augmented generation (RAG) and hybrid AI architectures
- Partner with client stakeholders to translate analytical insights into clear, actionable recommendations and measurable outcomes
We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role’s business requirements, this is a hybrid position requiring 3 days a week in a client or Cognizant office in Australia. We are open to hiring this role in Brisbane, Sydney or Melbourne. Regardless of your working arrangement, we are here to support a healthy work-life balance though our various wellbeing programs.
What You Must Have To Be Considered
- 8+ years of experience in technology consulting, data science, or applied machine learning in a client‑facing environment
- Strong hands‑on experience developing, testing, and deploying machine learning models using Python and modern ML frameworks
- Solid foundation in statistics, probability, and analytical techniques for model validation and decision support
- Experience working with cloud‑based data and ML platforms (e.g., Azure or AWS) and production ML pipelines
- Proven ability to communicate complex technical concepts to both technical and non‑technical stakeholders
- Experience with generative AI and large language models (LLMs), including prompt engineering and evaluation techniques
- Exposure to MLOps practices such as CI/CD pipelines, model monitoring, versioning, and governance
- Familiarity with tools such as Databricks, data lakes, feature stores, or containerized ML deployments
- Consulting experience leading client workshops, contributing to solution design, or supporting pre‑sales activities
- A collaborative mindset, comfort with ambiguity, and a strong focus on client outcomes
Key Skills
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