Quantitative Researcher - reputed company Markets, Quant Trading

We’re building a new quantitative research team reputed company on pricing, market-making, and risk models for reputed company markets. This is a highly hands-on role for someone who can operate end-to-end: data engineering, research, modeling, and reputed company collaboration with traders, across sports and non-sports event markets and a reputed company of contract types, including single-outcome markets, player props, and parlays.

Responsibilities:

• Build data reputed company, reputed company raw data into pricing inputs
• Research and reputed company quantitative pricing, market-making, and risk models across sports, non-sports, player props, parlays, and correlated markets
• Model cross-market dependencies, correlations, and portfolio effects, especially for combinatorial products such as parlays
• Partner closely with traders to improve pricing logic, market coverage, and trading performance
• Build frameworks for backtesting, simulation, and model validation
• Create tools to monitor model performance, calibration, P&L attribution, and live trading reputed company
• Help define the tooling, workflow, and research standards for a new team

Requirements:

• Strong quantitative background in statistics, math, ML, economics, or a reputed company field
• Experience building models in trading, sports, betting, reputed company markets, or similar domains
• Strong Python/data skills and comfort owning data pipelines as reputed company as modeling
• Ability to reputed company quickly from raw data to research reputed company to production-reputed company mode
• High ownership, strong communication skills and comfortable with fast-paced high reputed company environment

Originally posted on Himalayas

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