Cognizant Consulting is more than Cognizant's consulting practice - we're a global community of 5,000+ experts dedicated to helping clients reimagine their business. Blending deep industry expertise with technology advisory capabilities, we partner with organisations to deliver innovative, outcome-led solutions for some of the world's leading enterprises.
About the role
As a Data Science Consultant, you will make an impact by designing, building and deploying advanced AI, machine learning and generative AI solutions that solve complex business problems. You will be a valued member of Cognizant Consulting's AI & Data practice, working collaboratively with clients, fellow consultants, data engineers, and generative AI engineers across global delivery teams.
In this role, you will:
Design, build and optimise machine learning and AI models to deliver measurable business outcomes across client engagements.
Analyse, explore and transform complex datasets, applying statistical techniques, feature engineering and hypothesis-driven insights.
Develop, test and evaluate ML models using appropriate metrics, validation techniques and responsible AI practices.
Build and operationalise scalable ML pipelines using cloud-native and MLOps frameworks.
Collaborate with generative AI engineers to integrate traditional ML models with LLM-based solutions, including RAG architectures.
Work model
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 Melbourne, VIC. 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
Significant experience delivering data science and machine learning solutions within a consulting or professional services environment.
Strong proficiency in R, Python and modern ML frameworks (for example scikit-learn, PyTorch or TensorFlow).
Experience designing, training and evaluating supervised and unsupervised machine learning models.
Hands-on experience with cloud platforms (Azure and/or AWS), including ML services and data platforms.
Strong communication skills with the ability to engage both technical and non-technical stakeholders.
These will help you succeed
Experience with generative AI concepts, including large language models, prompt engineering and RAG patterns.
Exposure to MLOps practices such as CI/CD, ML pipelines, model monitoring and governance.
Knowledge of responsible AI practices including model explainability, fairness and drift monitoring.
A collaborative mindset, comfort working in ambiguity, and a strong focus on client outcomes.
We're excited to meet people who share our mission and can make an impact in a variety of ways. Don't hesitate to apply, even if you meet only the minimum requirements. Your transferable skills and unique experiences matter - and they may be exactly what this role needs.
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