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Senior Data Scientist

Expired
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Ingrity
Sydney NSW
hybrid
Full Time

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Posted 7 months ago
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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.