Work closely with clients and cross functional teams to define project scope, ensure technical feasibility, and drive delivery excellence.
Design and deliver bespoke data science solutions, shaping the technical direction of high-impact projects and solidifying our reputation as a leader in practical, measurable AI.
Map the end-to-end data science approach and design the associated software architecture for projects.
Drive the technical scoping and feasibility assessment of new projects.
Build strong client relationships by acting as a technical advisor and shaping the direction of current and future engagements.
Deliver bespoke algorithms and scalable software solutions that adhere to best practices for high-stakes decision-making.
Set the technical bar for the project team, ensuring the highest standards of code, rigour, and delivery quality (IC leadership).
Contribute to Faculty's thought leadership and reputation through teaching, public speaking, or open-source projects.
Requirements
Proven experience in a professional data science or quantitative academic role, underpinned by high mathematical and statistical competence.
Strong Python programmer, proficient in essential libraries (NumPy, Pandas) and a deep-learning framework (TensorFlow/PyTorch).
Solid grasp of core data science techniques (supervised/unsupervised learning, time-series, NLP, model validation) and the ability to innovate new algorithms.
Rigorous scientific and entrepreneurial mindset, translating complex business problems into a mathematical framework and measuring model impact upon deployment.
Exceptional communicator, adept at translating complex technical solutions into persuasive, actionable insights for senior and non-technical audiences.
Contribute to team success by project planning, assessing technical feasibility, estimating delivery timelines, and achieving measurable outcomes.