Lead Data Scientist

Introduction
We 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.

Role Summary
We 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.

This role aligns with our employee archetypes The Pathfinder. The Pathfinder carves the quickest route from idea to proof-of-concept, rapidly prototyping with Gen-AI toolchains, tests what works, and charts practical ways forward.

Responsibilities And Duties
Insight Translation

• AI 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 Enablement

• Account management: Manage client accounts, ensuring satisfaction, retention, and alignment of project deliverables with client goals.
• Project management: Leads 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. Able to effectively manage 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: Supporting the expansion of the team as we grow.

AI Orchestration

• Solution 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 Versatility

• Tool fluency: Demonstrate 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 Mindset

• Data engineering: Designs, builds, and maintains scalable data pipelines, robust data models, and production-grade machine learning solutions.

Ideal candidate
Skills & Experience

• Data 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: Proven experience in developing data models and working with modern data stacks (e.g., dbt, Airflow, Snowflake, Databricks, cloud platforms).
• Systems design: Demonstrated ability to design and implement AI application workflows by orchestrating multiple tools, APIs, and models to deliver end-to-end, production-ready solutions.
• Leadership Skills: Proven experience in mentoring and leading AI teams to achieve organisational goals.

Mindset & Capabilities

• Business storytelling and influence: Experienced at explaining findings and complex ideas to both technical and non-technical stakeholders.
• Resilience, flexibility and agility: Demonstrated the ability to adapt to a rapidly changing industry, ambiguous working environment and shifting project scope.
• Creativity and systems thinking: Experienced at integrating knowledge from diverse industries, functions, and technical disciplines to effectively address assigned tasks.
• Curiosity and lifelong learning: Stays updated on trends in AI, enjoys experimenting with new tools and technologies and actively shares knowledge with peers.

Nice to haves or wanting to learn on the job

• Startup or Scaleup experience: Have experience working in a fast-paced startup or scaleup technology business.
• Retail experience: Have experience working in the Retail industry.
• Tools: Exposure to AI agent architectures.

Our culture and core values
As we are still in our early stages, we believe cultivating our culture and core values is going to be critical to the success of our business. Our core values are human progress, iterate quickly, further together, be dependable, and have fun. We are looking for individuals who are attracted to these values and wanting to help shape our culture as we grow.

By 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

.