Senior Consultant

4 weeks ago

Sydney, Australia Deloitte Full time
Work on cutting edge Analytics & AI technologies in real world environments Flexible work arrangements – work in a way that suits you best Salary packaging – to suit your personal and financial circumstances

The Data Scientist will serve as a vital member of our team. You will be responsible for leveraging advanced analytical methods and generative algorithms to create synthetic data and derive actionable insights. This role offers a unique opportunity to work at the cutting-edge of Generative AI, alongside a multidisciplinary team including Data Engineers & Machine Learning Engineers and supports the Engineering Lead in the execution of the GenAI SDT program of work. 

What will your typical day look like?

Advising clients to help solve real-life business problems across diverse industries through use of data, cloud, analytics and AI technologies  Performing “hands on” statistical and machine learning modelling, computations, and data engineering  Involvement in identifying trends and innovation in deep learning, machine learning and related technologies 

Key Accountabilities:  

Analytical Modelling & Data Simulation: Utilise generative algorithms to create synthetic data sets for various modelling exercises, ensuring data integrity and relevance. Need to be responsible to support how we get ideas from prototype to scale quickly. Therefore, the ability not only to prototype but bring models into production is key Data Analysis & Interpretation: Analyse complex data sets and provide actionable insights that align with business objectives Research & Development: Stay abreast of emerging trends in Generative AI and contribute to the in-house knowledge base by actively participating in research initiatives Collaboration & Communication: Collaborate with different departments to identify business needs and devise solutions, effectively communicating technical concepts to non-technical stakeholders Ethical Considerations: Implement ethical guidelines in all data science projects, particularly those involving synthetic data, to ensure responsible and compliant data usage Technical Leadership: Mentor junior data scientists and collaborate with the data engineering team to ensure seamless data pipeline integration for generative models. 

Enough about us, let’s talk about you.

You may have all or some of the following skills / experiences: 

A minimum 5 years’ relevant work experience with data analytics, feature engineering and model development using market leading machine learning and deep learning techniques  A Master's degree or PhD in Data Science, Computer Science, Statistics, Mathematics, or a related field Solid expertise in data science libraries and frameworks like Scikit-learn, TensorFlow, or PyTorch & strong command of programming languages such as Python or R Experience with Big Data analytics, including Hadoop, Spark, graph analytics would be desirable Fluency in data querying and manipulation using cloud-based SQL and NoSQL database technologies Experience in utilising modern MLOps/DevOps approaches to manage and deploy models at scale on Azure (preferred), AWS or GCP.  Generative AI Expertise: Practical experience in Generative AI techniques such as GANs (Generative Adversarial Networks) or VAEs (Variational Autoencoders). utilising modern MLOps/DevOps approaches to manage and deploy models at scale on Azure (preferred), AWS or GCP Statistical Analysis: Robust understanding of statistical methods and data modelling techniques Communication Skills: Ability to articulate complex technical information to a diverse range of stakeholders.  Excellent interpersonal skills and a collaborative mindset Strong ethical grounding in data usage and AI implementation

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