Description
Design, build, and operationalize predictive models to inform securities investing, pricing, and valuation. Develop statistical and machine learning models for risk forecasting, asset optimization, pricing, and relative value analysis, delivering reliable insights and production-ready tools.
- • Document model requirements and specifications for data and engineering teams.
- • Provide analytical support to researchers, portfolio managers, or traders on signals, valuations, and data quality.
- • Define and monitor model and system performance metrics, including accuracy, latency, and drift.
- • Partner with engineers to develop, test, and validate modeling software against user requirements.
- • Research new datasets, features, and modeling techniques for financial use cases.
- • Maintain, recalibrate, and refactor production predictive models.
- • Produce clear reports and dashboards summarizing model methodology and results.
- • Interpret model outputs, explain drivers, and quantify uncertainty.
- • Build reusable modeling libraries and core analytics using statistical, machine learning, and econometric methods.
- • Define model specifications, feature sets, and data collection or labeling methods.
- • Elicit modeling needs from traders, portfolio managers, and risk teams to prioritize use cases.
- • Collaborate with quants and analysts on signals, market dynamics, and model integration.
- • Work with product and engineering to scope, validate, and implement models for new markets or products.
- • Develop tools for portfolio forecasting, optimization, performance attribution, P&L decomposition, and pricing.
- • Create challenger models and backtests to independently validate production models.
- • Apply statistical and machine learning techniques to pricing, trading, risk forecasting, and regulatory analytics.
- • Model pricing and risk for carbon credits and other environmental instruments.
- • Forecast climate-related financial impacts such as losses, insurance costs, and operational disruptions.
- • Develop predictive indicators of ESG performance and financial materiality.
- • Design models that inform hedging strategies for carbon exposure and transition risk.
- • Build evaluation models for green technologies and sustainable financial products.
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Financial Services
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O*NET occupational data (work activities, skills, knowledge).
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Last reviewed: Jan 2026
