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Totalis

Prediction Market Quantitative Trader

New York, NY, US · Not specified

Annual base salary
$140k – $250k USD
Equity
Not disclosed
Commitment
Full Time
Company stage
Not disclosed

Compensation as listed

$140K - $250K  •  0.50% - 2.00%

About Totalis

Totalis is building infrastructure for prediction markets.

We’re a small, technical team working at the intersection of financial systems, real-time data, and blockchain.

About the role

Totalis is building the derivative layer for prediction markets. We have a chain agnostic infrastructure for prediction markets. We are pioneering the financial products that become possible when derivatives can be built on top of them.

The team

Eric previously worked at Coinbase & Faire. Pravesh has built crypto infra across Eigen Labs, Squid Router, and other teams working on swaps, routing, and onchain systems.

You will work directly with the founders on the systems that define the company.

The work

We are hiring a Quantitative Trader to develop and operate the pricing and risk systems behind prediction market parlays and combo trades.

You will determine fair values for combos, model correlations between event contracts, set executable prices, and manage the portfolio risk. This role sits at the intersection of quantitative research, sports trading, derivatives pricing, and real-time market making.

What we are looking for

  • Experience with quoting RFQs on other prediction markets (Kalshi or Polymarket)
  • Familiar with exchange microstructure, liquidity, and adverse selection
  • Strong understanding of probability and statistics
  • Experience pricing or trading sports, prediction markets, or other trad-fi derivatives
  • Experience with one or more relevant modeling approaches, such as Monte Carlo simulation, copulas, graphical models, Bayesian networks, or multivariate probability models
  • Extremely high ownership and comfort operating in an early stage startup environment

Why Totalis

  • Work on a new financial product category at the intersection of prediction markets, sports trading, and derivatives
  • Price contracts that do not yet have standardized models or established market conventions, work with proprietary cross-venue market and RFQ data
  • Join an early team building foundational infrastructure for the prediction market ecosystem

Technology

Stack: TypeScript, Go, Postgres, Redis, and Rust smart contracts.

We build low-latency systems that keep off-chain and on-chain state correct under concurrent load.

Interview Process

1. Founder conversation

A short intro call to understand your background, your trading experience, and what you want next. We’ll share the problem we are solving and leave time for your questions.

2. Short take home exercise

A small project designed to show your approach to market making. You’ll walk us through your strategies and the tradeoffs you made.

4. Final working session

If there is strong mutual interest, we’ll bring you out to spend time with the team and work together.

5. Decision

We aim to make a clear decision and, when there is a strong fit, extend an offer within a week of the final conversation.

Source: Y Combinator. Confirm availability with the employer.

Apply through the original posting.

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