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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Research Director, AI Quantitative Modeling - **Company:** Idc Inc - **Location:** Needham, MA, United States (Remote available) - **Salary:** $77,350.0 - $139,800.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Business Analytics Applications, Python (Programming Language), Virtual Agents, Software Version Control - **Published:** September 26, 2026 - **Apply:** https://www.jofdav.com/jobs/59880501-research-director-ai-quantitative-modeling ## About the Role * Advanced quantitative training in mathematics, physics, statistics, operations research, or a closely related discipline, with a strong foundation in probability, statistical inference and numerical methods. * A track record of independently developing and validating financial, scientific or other quantitative models of complex systems. Experience should demonstrate how models were used to support forecasts, decisions or practical research outcomes. * Ability to choose and apply appropriate forecasting, simulation or optimization methods, explain their assumptions, and work with incomplete or noisy data without overstating the precision of results. * Strong scientific programming skills, preferably in Python, and experience translating mathematical ideas into working, testable code. Ability to develop reproducible analyses and work confidently with numerical libraries and structured data. * Current, regular use of agentic AI tools such as OpenAI Codex, Anthropic Claude Code, or comparable systems in their current role or daily life. Candidates must be able to discuss concrete workflows and explain how they verify generated code and analytical outputs. * Ability to learn unfamiliar technical and economic domains, challenge assumptions constructively, and work with subject matter experts to connect models with the systems they represent. * Clear written and verbal communication, including the ability to explain model logic, uncertainty and limitations to colleagues who do not share your mathematical background., * A PhD in mathematics, physics, statistics, operations research, or another relevant quantitative field is strongly preferred. Equivalent depth of research expertise demonstrated through applied work will also be considered. * Experience in quantitative research or model development at a hedge fund, investment bank, asset manager, or a comparable analytical environment. Relevant backgrounds also include scientific research and industrial modeling. * Experience developing models of costs, investment returns, productivity or economic impact, or turning research methods into reusable analytical tools. * Deep prior expertise in the technology industry or a particular customer sector is not required. Intellectual curiosity and the ability to learn the economics and technical characteristics of AI are essential. ## Description IDC is seeking a Research Director to develop the quantitative models that underpin our AI Economics research. The initial focus will be on modeling the cost and economic value of AI with scope to contribute to a broader range of modeling and forecasting projects as the team's research develops. This is a hands-on quantitative research role. You will translate complex questions into mathematical models, implement and test them in code, and develop methods that colleagues can reuse. Most of your time will be spent on model development, empirical analysis and validation, working with IDC's industry experts. You will also contribute to selected client discussions and presentations where your technical expertise is needed. Responsibilities * Design and develop models of complex systems with multiple interacting variables, nonlinear relationships and changing conditions. Frame research questions, select appropriate methods, and make assumptions, dependencies and limitations explicit. * Build AI cost models covering development, deployment and operation. Separate initial investment from recurring costs, and examine how workload, scale, utilization, technology choices and operating requirements affect total and unit costs over time. * Develop models of AI's economic value, including productivity, cost savings and revenue effects. Define baselines, account for adoption and implementation costs, and avoid double counting. Distinguish capacity released from cash savings and forecast benefits from measured results. * Create forecasts, simulations and scenarios that capture uncertainty and interactions between drivers. Use sensitivity analysis and stress testing to identify which assumptions matter most and where conclusions become unreliable. * Identify, assess and combine data from IDC research and other relevant sources. Work with subject matter experts to establish defensible inputs, address gaps and separate observed evidence from assumptions. * Calibrate and validate models against available evidence. Test predictive performance where feasible, compare alternative approaches, investigate errors, and update models as new data becomes available. * Build reusable, documented research code and workflows with appropriate tests and version control. Use agentic AI to accelerate coding, analysis and experimentation while independently checking the resulting code, methods and conclusions. * Explain methodologies and findings clearly to research colleagues and, when needed, clients. Contribute quantitative analysis to IDC research outputs and extend the team's modeling capability into subsequent projects.