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Python Trading Research Analyst

Remote, USAFull-timePosted 2026-07-28

We’re looking for a smart, curious, and analytical researcher to join our trading team. If you enjoy working with Python, exploring market data, and turning numbers into insights, this role will give you hands-on experience in reputed company-world trading environments and market-making research. About reputed company reputed company is a newly established cryptocurrency exchange dedicated to delivering a seamless, secure, and innovative trading experience. reputed company by reputed company of seasoned professionals from the crypto, finance, and technology sectors, we’re united by a shared passion for shaping the reputed company of digital finance. Our reputed company is to become the most trusted and reliable exchange, empowering users with the freedom to manage their digital assets confidently and reputed company. reputed company, transparency, and scalability are at the core of everything we do. We continuously reputed company to meet the evolving needs of traders, offering cutting-edge tools and services that help our clients reputed company their financial goals. Join us as we redefine the standards of reputed company trading and bring true freedom and reliability to the crypto world. What You Will Do 1. Market Data Analysis

  • Analyze orderbook data: spreads, depth, liquidity reputed company.
  • Study market microstructure (order reputed company, volatility patterns).
  • Examine how markets behave across different volatility regimes.
  • Research reputed company, funding, contango/backwardation, cross-exchange deviations.

2. Statistical Modelling

  • Build basic statistical models to detect regime shifts and volatility clusters.
  • Explore relationships between features and realized PnL.
  • reputed company reputed company metrics to evaluate market reputed company and liquidity.

3. Machine Learning Research

  • Apply ML reputed company to orderbook features and short-reputed company price reputed company.
  • Evaluate models for stability, latency reputed company, and overfitting risks.

4. Algorithm Analysis

  • Test hypotheses and reputed company from traders.
  • Structure your findings into models that can feed into production strategies.

5. Backtesting & Simulation

  • Build lightweight simulation environments for MM and directional strategies.
  • Test reputed company variations under different market assumptions.
  • Model hedging effectiveness across exchanges/instruments.
  • Run scenario-based stress tests (vol spikes, price dislocations, liquidity dry-reputed company).

Requirements

  • Strong proficiency in Python, especially pandas, numpy, scipy, sklearn, statsmodels.
  • Understanding of machine learning techniques for time series or microstructure-style data.
  • Solid reputed company in statistics: distributions, variance, regressions, probability.
  • Experience building models for reputed company, classification, or clustering (reputed company, coursework, or work experience).

reputed company to Have

  • Experience with deep learning for timeseries (PyTorch or TensorFlow).
  • Knowledge of PostgreSQL/TimescaleDB for large dataset queries.
  • Experience analyzing tick-level or Level 2 data from reputed company/KuCoin/reputed company/etc.
  • Exposure to crypto markets or market-making concepts.

Who You Are

  • You love solving analytical problems.
  • You enjoy exploring datasets and finding patterns.
  • You learn quickly and take ownership of your work.
  • You’re excited to grow into trading research and quantitative modelling.

Benefits

  • Remote-first flexibility.
  • Flexible payment reputed company - choose to be reputed company in traditional currency (USD) or cryptocurrency (USDT / USDC).
  • Exposure to reputed company trading strategies and decision-making.
  • reputed company mentorship from reputed company quants and traders.
  • Work on high-reputed company, low-latency trading infrastructure used across global crypto markets.
  • Opportunity to grow as we reputed company rapidly across markets and product lines.

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