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
Build the trusted data foundation that powers market intelligence, research, reporting, and production decision systems.
You will make heterogeneous event, market, and exposure data suitable for repeatable risk research and product delivery. Source provenance, time alignment, versioning, and corrections matter as much as throughput. You will work with researchers to ensure that an index value can be traced back to the observations and transformations behind it.
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
- Design batch and streaming pipelines for high-volume market and alternative data.
- Define reliable data models, quality checks, lineage, and observability.
- Improve storage, transformation, and query performance across analytical workloads.
- Partner with researchers and engineers to make datasets easy to discover and use.
- Build point-in-time datasets and lineage for event and market inputs, with explicit policies for late data, revisions, missing values, and reproducible research snapshots.
- 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
- Experience building and operating production data pipelines and warehouses.
- Strong SQL and Python skills plus familiarity with modern orchestration and cloud data tools.
- A practical understanding of schemas, testing, data quality, and distributed processing.
- Experience with real-time or financial data is an advantage.
- 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.