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Who we’ll hire

We build rules-based market signals and the quantitative research behind them. We hire people who do serious analytical, engineering, or distribution work.

Research

Quantitative Analyst

Toronto (Remote)

Own the analytical layer of the company: study how the signal behaves across regimes, quantify where it works and where it breaks, and turn that evidence into work that sharpens both the product and the Academy. This role is less about frontier research for its own sake and more about disciplined market analysis that holds up under scrutiny.

What you'd do
  • Analyze signal quality across market regimes, time windows, and failure cases, with a clear view of what is robust and what is conditional
  • Measure hit rate, forward return shape, drawdown behavior, and false-positive patterns across the full history
  • Build repeatable analytical workflows in Python or R that make new questions easy to test and old conclusions easy to revisit
  • Evaluate new indicators, filters, and market features that could improve the read without bloating the system
  • Turn quantitative findings into clear internal memos and Academy work that stay faithful to the evidence
  • Track current market context closely enough to flag setups, anomalies, and changes worth deeper analysis
What we'd look for
  • Degree in statistics, applied mathematics, finance, physics, computer science, or a similarly rigorous quantitative field
  • 3+ years in quantitative analysis, market research, or similarly analytical work where the standard of proof actually mattered
  • Comfort with Python or R, market data, and reproducible analysis workflows that can survive review by others
  • Strong statistical instincts and the discipline to distinguish a clean story from a true one
  • Clear writing that does not smuggle in more certainty than the evidence allows
  • Intellectual honesty, especially when the answer is inconclusive, messy, or inconvenient to the story
Research

Markets Analyst

Toronto (Remote)

Track the macro and market context that surrounds the signal: monitor regime conditions, document what the signal does and does not catch, and turn that ongoing analysis into Academy work that is honest about limits and useful to a disciplined investor.

What you'd do
  • Monitor macro conditions — VIX, Fed policy, labor, inflation — and maintain an ongoing read of where the market sits in the regime framework
  • Document signal performance in real time: what fired, what the context was, and what the outcome was as it matures
  • Write Academy articles and research notes that expand the educational layer without overstating what the signal can do
  • Identify macro or structural developments worth covering and propose content that would genuinely help a long-term ETF investor reason through them
  • Review historical episodes to surface patterns, edge cases, and failure modes worth documenting publicly
  • Maintain intellectual honesty in all written output — conclusions stated at the confidence the evidence actually warrants
What we'd look for
  • Degree in economics, finance, statistics, or a similarly analytical field
  • 2+ years tracking macro or equity markets in a research, analysis, or editorial capacity where accuracy mattered more than volume
  • Comfort reading and interpreting market data — price series, economic releases, Fed communications — without needing them translated
  • Clear, direct writing that does not dress up uncertainty as conviction
  • Genuine interest in how markets behave under stress, not just in normal conditions
  • The discipline to say nothing when there is nothing worth saying
Engineering

Data Engineer

Toronto (Remote)

Own the data and runtime layer that makes the research executable: ingestion, validation, persistence, internal APIs, and delivery infrastructure behind a product that has to be reliable every day it matters. In practice that means working across a Python research pipeline and a Cloudflare Worker stack that owns D1, webhooks, and customer-facing runtime behavior.

What you'd do
  • Maintain and extend the end-to-end signal pipeline, from Python-side computation through Worker-side ingestion, persistence, and delivery
  • Own TypeScript and SQL work inside a Cloudflare Worker architecture that handles Stripe, authentication, internal endpoints, and D1 reads/writes
  • Design and evolve schema, migrations, and internal API contracts so new product capabilities remain clear, auditable, and easy to reason about
  • Implement and validate new features, filters, and model components on market time-series without compromising reproducibility
  • Write documentation, review code, and promote architectural clarity so responsibilities stay clean across the Python and Worker boundaries
  • Keep the daily system observable, unit-tested, and resilient under failure, including the messy edge cases that only appear in production
What we'd look for
  • Degree in computer science, engineering, mathematics, or a related technical field
  • 3+ years building production systems in a data-heavy environment, ideally where reliability and auditability were non-negotiable
  • Strong Python plus enough TypeScript fluency to work comfortably in a serverless backend that owns real production state
  • Good engineering judgment around SQL schema design, API contracts, testing, code review, and change management
  • Experience with scheduled systems, external data sources, production reliability, and cloud infrastructure; Cloudflare familiarity is a plus
  • The ability to collaborate across research and engineering work without treating either side as someone else's problem
  • A bias for simple, inspectable systems with clear ownership boundaries over clever but fragile machinery
Open Application

If your work maps closely to one of these three functions, use this form to send a short note.