Lead Data Scientist

OverviewJoin or sign in to find your next jobWe believe human progress will come from augmenting AI to the way we work.
We help organisations scale results, not their headcount, with AI and automation.
We achieve this through two core business areas: AI Readiness and AI Agents.
If you want to get in on the ground floor of a fast-paced startup where your efforts have a direct impact on the success of our mission, we'd love to hear from you.The following role aligns with our employee archetype, The Pathfinder: the quickest route from idea to proof-of-concept, rapidly prototyping with Gen-AI toolchains, testing what works, and charting practical ways forward.Role SummaryWe are seeking a Lead Data Scientist with deep expertise in data science and AI, especially Generative AI, at an enterprise level.
The candidate will provide technical leadership to our consulting teams; project manage accounts and guide our clients through their AI journey.
Responsibilities include delivering AI Readiness Audits, providing strategic AI consulting to our clients, contributing to our product roadmap and guiding our technical team to build and deliver innovative and scalable AI solutions.
You'll drive business impact by solving real-world problems with advanced data science.ResponsibilitiesAI leadership: Develop and execute AI strategies to achieve business objectives and expand AI capabilities.Client recommendations: Translate insights from AI projects into actionable recommendations for clients.Research and innovation: Stay updated on industry trends, competitive landscape, and emerging technologies to inform AI strategies.Product roadmap: Gather and synthesise customer feedback and market trends to feed back into our product roadmap.Change EnablementAccount management: Manage client accounts, ensuring satisfaction, retention, and alignment of project deliverables with client goals.Project management: Lead end-to-end project management for data science initiatives, including scoping, planning, stakeholder communication, and delivery of outcomes aligned to business objectives.Stakeholder management: Manage multiple commercial and technical stakeholders effectively, including executive stakeholders.Team leadership: Lead, mentor, and grow a high-performing team of data scientists, ensuring project delivery excellence and professional growth.Work with ambiguity: Adapt to changing toolkits, models, and scopes, and manage volatile POCs and prototypes.Collaboration: Work closely with the sales, marketing, product, and delivery teams to align AI efforts with overall business objectives.Recruitment: Support the expansion of the team as we grow.AI OrchestrationSolution architecture: Design end-to-end AI systems that combine models, workflows, automation, and APIs.Use case delivery: Lead the development and deployment of AI initiatives that address real-world business needs.Prototyping: Rapidly develop and iterate on AI prototypes that demonstrate value and feasibility.Automation integration: Combine AI models with workflow automation and decision systems to streamline processes.Technical leadership: Guide the selection, development, and evaluation of ML and GenAI models for high-impact outcomes.Technical VersatilityTool fluency: Proficiency across AI/ML libraries, GenAI platforms, APIs, and deployment frameworks.Stack agility: Adapt quickly across cloud, open-source, and low-code/no-code toolchains to meet solution needs.Evolving landscape: Continuously research, evaluate new technologies and integrate promising tools into the delivery toolkit.Engineering MindsetData engineering: Design, build, and maintain scalable data pipelines, robust data models, and production-grade machine learning solutions.Ideal candidateSkills & ExperienceData science foundations: 7+ years of hands-on experience in data science or ML engineering, including hands-on experience with Generative AI.Technical proficiency: Proficient in Python, R, SQL; experience with frameworks like TensorFlow, PyTorch, LangChain.Engineering experience: Experience in developing data models and working with modern data stacks (e.g., dbt, Airflow, Snowflake, Databricks, cloud platforms).
Systems design: Ability to design and implement AI application workflows by orchestrating multiple tools, APIs, and models to deliver end-to-end, production-ready solutions.Leadership: Proven experience in mentoring and leading AI teams to achieve organisational goals.Mindset & CapabilitiesBusiness storytelling and influence: Explaining findings and complex ideas to technical and non-technical stakeholders.Resilience, flexibility and agility: Ability to adapt to a rapidly changing industry, ambiguous working environment and shifting project scope.Creativity and systems thinking: Integrating knowledge from diverse industries and disciplines to address tasks.Curiosity and lifelong learning: Stays updated on AI trends and shares knowledge with peers.Nice to have or learning on the jobStartup or scaleup experience: Experience in fast-paced startup or scaleup technology business.Retail experience: Experience in the Retail industry.Tools: Exposure to AI agent architectures.Privacy and policyBy applying for a role with us, you agree that we will collect and handle your personal information in accordance with our Privacy Policy, available at : Sydney, New South Wales, Australia
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