Teams at Jefferies

Lead and coordinate cross-site delivery for front-office equity derivatives technology. Design, implement, unit-test and enhance C#/.NET or Java trading applications, manage release planning, dependencies, RAID, stakeholder communications, and support validation, reconciliations and production issues.

Build AI, machine-learning, and statistical models to predict clinical-trial outcomes, regulatory results, and commercial potential. Analyze trial designs, endpoints, patient populations, treatment effects, safety, and subgroup data. Apply generative AI, LLMs, and NLP to scientific and regulatory information. Develop pipeline-monitoring tools, validate models, control bias and data leakage, and translate clinical and quantitative findings into investment conclusions supporting equity research, forecasts, valuations, and published analysis.

Leads FinOps for an enterprise AI program, establishing cost transparency, governance, forecasting, allocation, controls, optimization, and executive reporting. Partners with Finance, Engineering, Infrastructure, Procurement, Product, Risk, and business stakeholders to analyze AI consumption, model and vendor economics, improve financial outcomes, support budgeting and chargeback, and guide commercially informed architecture and purchasing decisions.