Data Scientist
2 days ago
New Role- Data Scientist
Location-
Sydney
Duration -
12-month duration.
Requirement –
Immediate. (for a good candidate we can consider 2 weeks' notice).
About the Role
As a Data Scientist in our team, you will be instrumental in solving real-world business problems using advanced data science techniques and cloud-native technologies. You'll work across diverse datasets, build scalable tools, and deploy solutions using AWS services including SageMaker, Glue, EMR, and Redshift.
Key Responsibilities
- Source, clean, and prepare large-scale datasets for analytics and operational use.
- Create productivity tools using Python and R scripts to streamline workflows and enhance the effective use of available models.
- Apply statistical and analytical techniques to extract insights and support decision-making.
- Build and deploy data-driven solutions using AWS SageMaker, leveraging asynchronous inference and batch transform pipelines.
- Collaborate with stakeholders to understand business priorities and translate them into data-driven solutions.
- Create clear and compelling visualisations and presentations for technical and non-technical audiences.
- Ensure responsible use of AI technologies by adhering to governance and ethical standards.
- Contribute to CI/CD pipelines for solution deployment and monitoring.
Preferred Skills & Experience
- Proficiency in Python, R, SQL, and experience with Spark or Snowflake.
- Hands-on experience with AWS services: SageMaker, Glue, EMR, S3, Redshift, DocumentDB.
- Familiarity with MLOps practices and model lifecycle management.
- Strong understanding of data engineering principles and cloud architecture.
- Exposure to frameworks and design concepts, with an understanding of how to treat
data as a product
. - Experience in GenAI, prompt engineering, and responsible AI guardrails is a plus.
- While building predictive models is not a core responsibility, having that skill set is considered an added advantage.
- Excellent communication and stakeholder engagement skills.
Domain Expertise
- Experience working with data across the
banking and financial services domain
, including products from
Retail, Institutional, and Business Banking
. - Exposure to
financial crime and transaction monitoring
use cases is highly preferred. - Understanding of regulatory and compliance considerations in financial data environments is desirable.
Ideal Candidate Profile
- A problem-solver with a growth mindset and a passion for data.
- Comfortable working in agile, cross-functional teams.
- Able to balance technical depth with business impact.
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