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. About INGRITY: We are a fast-growing, progressive Sydney-based data & analytics company. We service many large corporates and SMBs in the financial services sector, to derive value from data. At Ingrity, we are committed to building a diverse and inclusive workforce to deliver value to customers. As a value-driven organisation, we nurture and support our people by having a laser-sharp focus on skill and talent development, collaboration, and flexibility.
