A pairs / stat-arb equity trader at Maverick runs market-neutral or beta-neutral strategies on US equity relationships — pairs within the same sector, cointegrated baskets, or single-name long-short setups driven by mean-reversion or fundamental divergence. This is the most quantitative trader role at the firm; expect to be doing real statistical work, not just looking at charts.
Tulsa, OK: Tulsa's economy is built around energy (BOK Financial, Williams Companies) and aerospace. The metro has actively recruited remote workers with relocation incentives over the last several years. Central Time alignment with US markets, very low cost of living.
What you'll trade: Long/short pairs within sectors (e.g., two banks, two airlines, two oil majors), basket trades against ETF benchmarks, and divergence trades when a fundamentally similar pair has drifted apart on price. We do not run ultra-high-frequency stat-arb — the firm's infrastructure is professional but not co-located.
Risk framework: Pairs strategies look low-risk until a relationship breaks — at which point both legs can move against you simultaneously. Maverick traders run defined max-loss per pair and require fundamental review when statistical signals fire on names with company-specific news.
Why Maverick funds this role: Pairs and stat-arb provide the firm with a low-beta P&L stream that diversifies away from directional and pure-vol books. Maverick funds traders here because the strategy contributes to firm-level Sharpe even when its individual returns are modest.
Traders with quantitative training — Python, R, or strong Excel comfort with regressions People who can read a cointegration breakdown as a 'get out' signal, not 'add to the trade' Candidates who understand the limits of statistical edge in single-stock relationships Traders patient with sample sizes — single pairs can take weeks to play out #J-18808-Ljbffr