Senior Data Scientist
Expired
This role has expired and is no longer accepting applications. Browse similar roles →
Ingrity
Sydney NSW
hybridFull Time
Apply for this job
Posted 5 months ago
This role is expired
These roles are hiring now
View all similar roles →Data Consultant (12-month Fixed term Contract)
NAB
Sydney, NSW | Brisbane, QLD | Melbourne, VIC
hybrid- Fraud analytics: develop models, rules & insights for fraud prevention
- Extensive data science/analytics experience in financial services (fraud focus)
- Statistical techniques, modelling tools, fraud typologies, large datasets
Posted 2d ago
Senior Data Consultant (12-month Fixed term Contract)
NAB
Sydney, NSW | Brisbane, QLD | Melbourne, VIC
hybrid- Develop & deploy ML models for fraud prevention, detection & intervention
- Extensive experience in data science/analytics in financial services
- ML, statistical modelling, fraud domain expertise, production-ready models
Posted 2d ago
Lead AI Enablement Scientist
Resmed
Sydney, NSW
hybrid- Enable AI/ML products via data discovery, assessment & labelling strategy
- PhD with 3+ years or Master's with 7+ years in data science/engineering
- Python, SQL, AWS, Snowflake, time-series data, signal processing
Posted 3d ago
Data Science Manager - GTM Sales
Canva
Sydney, NSW | Austin, Texas
hybrid- Lead analytics for B2B Sales & Customer Success, coach 4 data scientists
- Multiple years B2B SaaS data science + leadership experience
- SQL, Snowflake, dbt, BI tools, GTM metrics, forecasting, AI automation
Posted 3d ago
About the Job
We are looking for a Senior Data Scientist to join our team and collaborate with a leading organization using data and AI to deliver measurable business results. This hands-on role offers the opportunity to lead high-impact AI initiatives, shape data strategy, and mentor emerging data science talent.
Key Responsibilities:
Lead High-Impact Data Science & AI Initiatives:
- Deliver technically complex AI and Data Science projects that create measurable business value.
- Build solutions such as Generative AI models, Intelligent Process Automation, and AI-enabled decision support to improve processes, optimize costs, and enhance customer experience.
- Ensure solutions are production-ready, scalable, and embedded into business processes.
Solution Design & Problem Solving:
- Collaborate with senior business stakeholders to understand challenges and design innovative, first-principles-based solutions.
- Translate business problems into actionable AI and analytics strategies that drive tangible outcomes.
- Extend solutions to production systems for operational impact.
Thought Leadership & Advocacy:
- Provide guidance and mentorship to team members and broader analytics community.
- Communicate complex AI concepts to technical and non-technical audiences, including senior executives.
- Maintain external industry networks and bring emerging Data Science & AI practices into the organization.
- Demonstrate the value of AI through prototypes, presentations, and showcases.
Team & Ecosystem Contribution:
- Mentor junior data scientists and promote best practices in analytics delivery.
- Influence the development of platforms, tools, and workflows that support scalable AI solutions.
- Support a collaborative, high-performing team environment.
Stakeholder Engagement:
- Work closely with Principal Data Scientists, technical leads, and data engineering teams.
- Collaborate with business leaders, engagement managers, and solution architects to align AI initiatives with strategy.
- Engage with external partners and vendors on advanced Data Science & AI projects.
Required Qualifications:
Technical Experience:
- 7+ years of hands-on experience in Data Science, AI, or closely related disciplines - Required.
- Proven track record developing and productionizing machine learning pipelines - Required.
- Experience with Python programming and ML pipeline optimization - Required.
- Deep knowledge of machine learning algorithms and deep neural networks - Required.
- Experience with workflow automation platforms including UiPath - Required.
- Hands-on experience with Generative AI, including POCs and prototypes - Required.
- Experience with cloud-based analytics platforms (e.g., Databricks).
- Experience building low-code AI agents.
Core Technical Skills:
- Comprehensive expertise across diverse data science and AI techniques applicable to financial services or similar complex domains.
- Strong understanding of what works in practice versus theoretical approaches.
- Excellence in end-to-end solution design, balancing technical innovation with user-centered design principles.
- Ability to solve novel analytical problems without established patterns.
- Deep knowledge of ML engineering, including parallel computing, distributed processing frameworks.
- Familiarity with low-code/no-code platforms for democratizing AI development.
- Practical expertise in algorithm design and AI system architecture.
Professional Attributes:
- Pragmatic approach that balances technical excellence with practical delivery constraints.
- Strong work ethic and proactive engagement.
- Genuine commitment to team success and knowledge sharing.
- Research-oriented mindset with intellectual curiosity and analytical rigor.
- Exceptional communication skills across technical and non-technical audiences.
- Outstanding presentation abilities (verbal, written, and visual).
- Flexibility to work across different delivery modes (rapid innovation to formal project governance).
- Unwavering focus on measurable business outcomes and tangible value creation.
- Commercial acumen and understanding of business performance drivers.
Education:
- Bachelor's degree in a technical field (Data Science, Machine Learning, Statistics, Mathematics, Computer Science, Engineering, or related discipline) - Required.
- Postgraduate degree (Master's or PhD) in a relevant quantitative field - Highly Desired:
- Candidates without postgraduate qualifications should demonstrate equivalent expertise through substantial industry experience.