About Time Seventeen
We give risk a price. We create state prices for tail events.
The world contains a large class of risks that determine where capital flows yet have no price today. Global supply chains are being reconfigured, while the geopolitical discount rates that inform consequential decisions remain difficult to quantify. Time Seventeen is building tradable synthetic indices and term structures for these risks.
Time Seventeen is infrastructure for geopolitical risk and catastrophe risk. We give risk a price. We create state prices for tail events. Our ambition is to turn fragmented judgments about individual events into continuous risk prices, then bring those prices into institutional valuation, trading, and risk-transfer workflows.
Our work connects event definitions, probabilistic forecasting, market data, index methodology, and execution infrastructure. We explore how prediction markets, actuarial models, insurance and reinsurance structures, and blockchain-based DeFi can contribute to a common language for uncertain outcomes. The challenge is to make risk legible across different horizons, exposures, and market participants, while keeping assumptions and limitations explicit.
Building this infrastructure requires more than a compelling forecast. Data must be traceable, events must have defensible resolution rules, methodologies must survive scrutiny, and products must account for liquidity, basis risk, operational resilience, and applicable legal constraints. We want institutions to be able to understand a risk price, challenge its construction, and assess how it relates to the exposure they actually hold.
We are building a focused team across research, engineering, markets, and risk. We value people who can move between deep specialist work and the practical decisions needed to build a company: identifying the important question, testing an approach, communicating the evidence, and carrying the result into a usable system.
About the role
Set the research agenda for predictive systems and lead a focused team from rigorous experimentation to measurable production impact.
You will lead research on how uncertain geopolitical and catastrophe events can be represented as calibrated, continuously updated forecasts. The work connects probabilistic reasoning to index construction and market evidence. You will help the team distinguish signal from narrative and design evaluations that remain useful when events are rare.
You will work closely with colleagues across research, engineering, markets, and risk. We expect you to clarify assumptions early, share intermediate evidence, and make decisions that account for the users and systems downstream of your work. The scope can evolve as we learn, but each initiative should have a clear owner and a concrete result.
What you'll do
- Translate broad prediction goals into a small number of testable research programs.
- Set standards for evaluation, calibration, reproducibility, and scientific communication.
- Guide researchers through experiment design, analysis, iteration, and deployment.
- Partner with engineering and product leaders to turn validated work into durable systems.
- Set research standards for calibration, temporal validation, event resolution, and sensitivity analysis, and compare forecasts against meaningful baseline models.
- Document important decisions, assumptions, and limitations so that colleagues can review the work and extend it without relying on undocumented context.
What we're looking for
- A strong research record in machine learning, forecasting, statistics, or a related field.
- Experience managing or technically leading researchers on ambiguous problems.
- Excellent judgment about evidence quality, model limitations, and research prioritization.
- The ability to move quickly while maintaining analytical rigor.
- An ability to explain complex work clearly, distinguish evidence from assumptions, and update your view when new information warrants it.
- Interest in building infrastructure for geopolitical and catastrophe risk, with a willingness to learn the financial and technical context beyond your own specialty.
What success looks like
- Deliver a well-defined piece of work that advances a real research, product, or institutional workflow, with acceptance criteria agreed with the team.
- Make the quality of your work inspectable through appropriate analysis, tests, documentation, or operational evidence.
- Create reusable methods and clear handoffs that help the wider team work more effectively.
Location & working arrangement
This role is based in Hong Kong. Please include your location, availability, and any working-arrangement requirements in your application.
How to apply
Tell us why this problem interests you and share examples of relevant work. Where possible, describe what you personally owned, the decisions you made, and what you learned. Please exclude confidential information belonging to previous employers or clients.
How we work
Time Seventeen is a focused, high-ownership team. We value clear thinking, direct communication, careful execution, and people who carry important work through to a result. We expect colleagues to surface inconvenient evidence, ask precise questions, and make the limits of their work explicit. Strong specialist judgment matters, as does the willingness to understand how your work affects research, markets, engineering, and risk. We prefer useful documentation and clear decisions to unnecessary process.