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Quantitative Jobs in Berkeley, CA
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Quantitative • berkeley ca
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Senior Quantitative Developer
Swish AnalyticsSan Francisco, California, United States- Promoted
Transactional Quantitative Analyst
Cooley LLPSan Francisco, CA, United StatesQuantitative Risk Estimation Engineer
KodiakSan Francisco, California, USAQuantitative Researcher
San Francisco StaffingSan Francisco, CA, United States- Promoted
- New!
Quantitative Developer
Manifold TechnologiesBerkeley, California, United States- Promoted
- New!
Quantitative Developer
Midpoint MarketsSan Francisco, California, United States- Promoted
Quantitative Sales Associate
DatabentoSan Francisco, CA, US- Promoted
- New!
Monetization Research Lead, Quantitative
PinterestSan Francisco, California, United StatesQuantitative Researcher Private Assets
MSCISan Francisco, CA, United States- Promoted
Quantitative Data Scientist
PlaceholderSan Francisco, CA, United States- Promoted
Quantitative Intelligence Analyst
OpenAISan Francisco, CA, United States- Promoted
- New!
Quantitative Developer - AI Implementation
WorldQuantSan Francisco, California, United States- Promoted
- New!
Quantitative UX Researcher, Search
GoogleSan Francisco, California, United States- Promoted
Senior Quantitative Developer - BQuant
Bloomberg L.P.San Francisco, CA, United States- Promoted
Quantitative Risk Researcher
DivineSan Francisco, CA, United States- Promoted
- New!
Quantitative Developer
Evolve GroupSan Francisco, California, United States- Promoted
- New!
Software Engineer, Quantitative Evaluations
WaymoSan Francisco, California, United StatesQuantitative Geneticist, Predictive Breeding
OhaloSan Francisco, CA, US- Promoted
Senior Quantitative Developer - BQuant
Bloomberg New Energy FinanceSan Francisco, CA, United States- software development manager (from $ 220,000 to $ 273,000 year)
- nuclear medicine (from $ 153,470 to $ 250,984 year)
- veterinarian (from $ 115,000 to $ 250,000 year)
- python developer (from $ 135,000 to $ 244,125 year)
- office administrative assistant (from $ 47,840 to $ 243,900 year)
- vp of engineering (from $ 68,428 to $ 237,500 year)
- embedded systems engineer (from $ 133,875 to $ 222,134 year)
- product director (from $ 157,500 to $ 220,750 year)
- applications engineer (from $ 149,709 to $ 218,500 year)
- startup (from $ 136,250 to $ 216,250 year)
- New York, NY (from $ 115,248 to $ 220,000 year)
- Houston, TX (from $ 105,000 to $ 212,500 year)
- San Francisco, CA (from $ 120,050 to $ 205,000 year)
- Philadelphia, PA (from $ 100,454 to $ 200,768 year)
- Boston, MA (from $ 108,000 to $ 184,513 year)
- Chicago, IL (from $ 109,358 to $ 175,000 year)
- Los Angeles, CA (from $ 90,000 to $ 168,360 year)
- Phoenix, AZ (from $ 97,600 to $ 152,315 year)
The average salary range is between $ 100,000 and $ 200,000 year , with the average salary hovering around $ 139,133 year .
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Senior Quantitative Developer
Swish AnalyticsSan Francisco, California, United States- Full-time
Senior Quantitative Developer
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Senior Quantitative Developer
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Swish Analytics .
Company Description
Swish Analytics is a sports analytics, betting, and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer / enterprise clients.
Role Overview
You’ll architect and build the core trading systems that execute our fair value models across sports betting exchanges at scale. This is a systems engineering role focused on real-time decision-making, multi-venue orchestration, and low-latency execution under production constraints.
Real‑Time Trading Engine Architecture
Design event-driven trading systems that consume fair value models and market data to make sub-second execution decisions
Build the core logic for comparing fair values against live market prices and determining when / where to trade
Implement asynchronous order generation, submission, and cancellation workflows across multiple venues with different latency profiles
Design state machines for order lifecycle management (pending, accepted, filled, cancelled, rejected) with proper event ordering and idempotency
Multi‑Venue Execution & Routing
Build venue-specific integrations (WebSocket connections to Matchbook, Kalshi; REST API adapters for Betfair; FIX protocol handlers)
Implement intelligent order routing that selects optimal venues based on liquidity, fees, latency, and position constraints
Design coordination logic for managing orders across multiple venues when a single bet spans several platforms
Handle venue-specific quirks (rate limiting, connection drops, partial fills, odds movement during submission)
Position & Risk Management Systems
Build real-time position tracking systems that aggregate exposure across all venues, markets, and event types
Implement global liability management that enforces risk limits while maximizing capital utilization
Design systems
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