Provide technical leadership to consulting teams and project manage accounts.
Guide clients through their AI journey and deliver AI Readiness Audits.
Provide strategic AI consulting and contribute to the product roadmap.
Drive business impact by solving real-world problems with advanced data science.
Lead the development and delivery of innovative and scalable AI solutions.
Adapt to changing toolkits, models, and scopes, and manage volatile POCs and prototypes.
Mentor and grow a high-performing team of data scientists.
Requirements
7+ years of hands-on experience in data science or ML engineering, including hands-on experience with Generative AI.
Proficient in Python, R, SQL; experience with frameworks like TensorFlow, PyTorch, LangChain.
Proven experience in developing data models and working with modern data stacks (e.g., dbt, Airflow, Snowflake, Databricks, cloud platforms).
Demonstrated ability to design and implement AI application workflows by orchestrating multiple tools, APIs, and models to deliver end-to-end, production-ready solutions.
Proven experience in mentoring and leading AI teams to achieve organisational goals.
Experienced at explaining findings and complex ideas to both technical and non-technical stakeholders.
Demonstrated the ability to adapt to a rapidly changing industry, ambiguous working environment and shifting project scope.
Experienced at integrating knowledge from diverse industries, functions, and technical disciplines to effectively address assigned tasks.
Stays updated on trends in AI, enjoys experimenting with new tools and technologies and actively shares knowledge with peers.
Benefits
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.
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.
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