
Senior Consultant | Risk Data & AI
- Sydney, NSW
- Permanent
- Full-time
- A dynamic environment that will give you the opportunity to grow your career
- An energetic and supportive culture that puts people first
- Flexible ways of working
- Build high-performance data pipelines using advanced data engineering and ETL practices for effective client solutions.
- Leverage AI, especially generative AI, to turn client risks into opportunities.
- Maintain and deploy analytical assets to support clients and expedite delivery.
- Develop and deploy practical models from large, ambiguous quality datasets to drive customer outcomes and inform senior decision-making.
- Perform complex feature engineering on risk-related data to enhance model performance.
- Translate complex technical solutions and insights into clear, business-friendly language for colleagues and clients.
- Display a passion for continual self-improvement and innovative problem-solving for clients.
- Collaborate with the Financial Risk & Regulatory team, providing mentorship to new team members.
- Maintain open communication to understand expectations and identify areas for improvement for both personal and team development.
People working across a wide range of industries and the public sector, our team advise, implement and deliver analytics to support decision-making. Our team is an inclusive, dynamic and growing team committed to driving innovation, delivering client outcomes and making an impact that matters. The strength of our team lies in the diversity of the background and skillset of each member, fostered in a collaborative environment.Enough about us, let's talk about you.You must have the following skills / experience:
- A strong foundation in Python and SQL
- Hands-on experience with data science libraries such as Pandas, NumPy, SciPy for data manipulation, Scikit-learn for traditional ML models, and TensorFlow/ PyTorch for deep learning.
- Experience in data engineering, working with SQL, PySpark, and ETL pipelines to process large datasets efficiently.
- A data visualization mindset, using Power BI to create insightful dashboards with DAX and Power Query.
- Strong stakeholder management skills, with the ability to communicate complex AI-driven insights to technical and non-technical audiences.
- Experience in building machine learning models and deploying them at scale.
- Understanding of Generative AI, including LLM fine-tuning, embeddings, and prompt engineering using Hugging Face Transformers, LangChain, and vector databases.
- Knowledge of Natural Language Processing (NLP) with libraries such as spaCy, NLTK, and transformers to develop text analytics, sentiment analysis, and entity recognition solutions.
- Cloud expertise with AWS (S3, Lambda, SageMaker) and Azure (Databricks, AI Studio, Synapse Analytics) for scalable ML solutions.
- Proficiency in GitHub version control, CI/CD pipelines, and collaborative ML development.