We build software and quantitative systems for sports contracts offered through CFTC-regulated prediction markets.

We're looking for a strong software engineer who can take ownership of systems involving live sports data, contract pricing, player-performance markets, automation, and trading operations.

Engineering ability is the foundation of this role.

What you'll work on

Build and improve systems for live sports and player-performance markets

Develop reliable pipelines for processing real-time sports and market data

Turn quantitative ideas and operational requirements into production software

Improve pricing formulas, market behaviour, monitoring, and automation

Build internal tools that make trading and modelling workflows faster and more reliable

Investigate data discrepancies and unexpected system behaviour

Refactor existing systems to improve their speed, clarity, and reliability

Take ownership of projects from an ambiguous problem through production deployment

Work directly with people responsible for trading, modelling, and business decisions

Availability expectations

Sports don't happen on a 9 to 5 schedule. Games run on evenings, weekends, and holidays, and markets need to keep working through all of it. You should be comfortable with:

Providing on call or hands on support during evenings, weekends, and holidays when major games or events are live

Responding quickly when something breaks during a live market, regardless of time of day

Occasional schedule flexibility around high volume sports periods (playoffs, marquee events, etc.)

This isn't a constant state, but it's a real and recurring part of the job. Please only apply if this schedule works for you.

What we're looking for

Strong software engineering fundamentals

Experience building and maintaining production systems

Evidence that you can personally take a meaningful project from idea to completion

Ability to work independently without perfectly defined requirements





Sound judgment about correctness, reliability, and technical trade offs

Comfort working with APIs, databases, data pipelines, and automated processes

Ability to understand an existing system before changing it

Explicit communication and a willingness to identify risks early

Genuine interest in sports, prediction markets, modelling, or trading

Beyond engineering, we're particularly interested in demonstrated ability in at least one of these areas:

Quantitative modelling, forecasting, probability, or statistical analysis. Including backtesting, calibration, or measuring predictive performance.

Prediction markets, trading, pricing, execution, or risk management. Including regulated prediction markets, event contracts, market making, or automated trading/execution systems.

Also valuable: sports market or player performance modelling, real time or event driven applications, data ingestion from inconsistent third party sources, and personally building and operating a model, bot, analytics product, or trading system.

You do not need conventional experience across every area. Some of the strongest candidates have built forecasting models, prediction market bots, automated trading systems, or sports analytics products independently.

Our current stack is Kubernetes, FastAPI, Python, React, and TypeScript. Experience with that stack is helpful, but strong engineering ability and evidence that you can learn quickly matter more than matching every technology.

What success looks like

Within your first few months, you should be able to:

Understand the major components of our sports market systems





Take ownership of a meaningful production feature

Deliver reliable work with decreasing levels of direction

Improve the quality and maintainability of the systems you touch

Contribute useful thinking beyond implementation, whether in modelling, market behaviour, trading workflows, or product design

Who will thrive here

You'll likely enjoy this role if you're a builder who likes problems that cross traditional boundaries.

You may be an engineer who thinks quantitatively, an engineer who follows markets, or someone who has learned by building and operating your own systems.

We care more about demonstrated ability, ownership, judgment, and rate of learning than credentials alone.

Application requirements A resume alone is not sufficient. Please also submit a case study (800 words max) about one system you personally built.

Tell us what it does, how you built it, and what happened once it was real. We're especially interested in what you learned or would do differently, particularly anywhere the system touched live or changing data, probability, pricing, or risk.

Include a link to the system itself: repo, live product, or write up. If it's confidential, describe it precisely without sharing protected details.

If you worked on it with others, say plainly what was yours.

We're not looking for a resume restated in prose. We're looking for the project that best shows how you think. Pick the one that does that, even if it's not your most "impressive" one on paper.

Applications without a case study and a link will not be reviewed. Please don't submit proprietary code or confidential information belonging to another organization.

To apply, email your resume and case study to [email protected].

Pay: $90,000.00-$130,000.00 per year

Benefits

- Flexible schedule
- On-site parking
- Profit sharing

Work Location: Hybrid remote in Edmonton, AB T5L 4V5

📌 Software Engineer — Sports Prediction Markets (Edmonton)
🏢 Kachan Research
📍 Edmonton