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14 дней назад

ML / Quant Researcher (Middle / Senior)

12 000$
Формат работы
remote (Global)
Тип работы
fulltime
Грейд
middle/senior
Английский
b2
Страна
Serbia
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
ML / Quant Researcher (Middle / Senior) (ML/Trading): Developing machine learning and quantitative models for forecasting and signal generation using time-series and real-time market data with an accent on statistical research, hypothesis validation, and strategy improvement. Focus on building and testing trading models, analyzing market structure, and working with research and backtesting infrastructure.

Location: Remote setup with flexible hours. The main office is in Serbia, while the team is distributed.

Salary: Up to $12,000 net per month plus bonuses.

Company

hirify.global is a small, low-bureaucracy trading-focused team working on machine learning and quantitative research.

What you will do

  • Develop machine learning and quantitative models for forecasting and signal generation.
  • Analyze time-series and real-time market data.
  • Test research hypotheses and improve existing trading strategies.
  • Work with research and backtesting infrastructure.
  • For senior candidates, shape new research directions and trading strategies.

Requirements

  • Strong knowledge of Python and the machine learning stack, including NumPy, numba, PyTorch or JAX, and scikit-learn.
  • Basic understanding of C++ or the ability to read C++ code.
  • Strong mathematical and statistical background.
  • Experience with time-series data, market data, hypothesis testing, signal or model validation, and quantitative research.
  • Understanding of trading principles, market structure, and market data.
  • Middle candidates need experience in ML or quantitative research; senior candidates need proven experience in trading, algorithmic trading, or quantitative research.

Nice to have

  • Production C++ development, HFT, arbitrage, market-making, or low-latency systems experience.
  • Competitive programming or a strong academic background, including ICPC, Kaggle, or Yandex SHAD.
  • Publications at top-tier machine learning conferences or strong results in ML, data science, or quantitative competitions.
  • Experience developing complex machine learning or deep learning models.

Culture & Benefits

  • Remote work with flexible hours.
  • Small, low-bureaucracy team with fast decision-making and rapid hypothesis testing.
  • Distributed team with a main office in Serbia.
  • Collaboration with specialists from leading universities and technical backgrounds.

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