Head of Data Strategy leading and developing data initiatives for Zurich's GI Business. Focusing on data strategy, governance, and analytics while fostering collaboration across teams.
About the role
- Lead Data Scientist providing technical leadership and strategic AI consulting for clients. Delivering innovative AI solutions and driving business impact in a hybrid work environment.
Responsibilities
- 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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