- Company Name
- BHFT
- Job Title
- Quantitative Researcher (MFT / ML Pipeline)
- Job Description
-
Job title: Quantitative Researcher (MFT / ML Pipeline)
Role Summary:
Design and maintain machine learning and feature engineering pipelines for Medium-Frequency Trading strategies. Conduct market research, develop and validate predictive models, and collaborate with quants, data engineers, and infrastructure teams to deploy models and refine performance.
Expectations:
* 1–2 years quantitative or data science experience in finance, trading, or applied machine learning.
* Strong grasp of machine learning workflows, statistics, time‑series analysis, and predictive modeling.
* Proficient in Python and libraries such as Pandas, NumPy, Scikit‑learn, and PyTorch.
* Detail‑oriented, analytical, self‑motivated, and able to communicate clearly in a remote team.
Key Responsibilities:
* Build, test, and optimize feature pipelines for MFT trading strategies.
* Perform data‑driven market research to uncover alpha signals across equities, futures, and other asset classes.
* Train, validate, and evaluate models on large historical datasets (OHLCV, tick data, order book).
* Develop proof‑of‑concept trading models and backtest hypotheses using scalable backtesting frameworks.
* Work with senior quants, data engineers, and infrastructure to ensure efficient data flow and model deployment.
* Monitor model performance, adjust for changing market conditions, and propose improvements.
* Contribute to continuous integration of data versioning and MLOps practices.
Required Skills:
* Machine learning pipeline development (feature engineering, model training, validation).
* Statistical analysis and time‑series forecasting.
* Python programming with data science stack (Pandas, NumPy, Scikit‑learn, PyTorch).
* Understanding of financial data structures: tick data, OHLCV bars, L2 order book.
* Strong analytical and problem‑solving abilities.
* Excellent written and verbal communication.
* Ability to work independently and collaboratively in a distributed environment.
Required Education & Certifications:
* Bachelor’s degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or related quantitative field.
* Master’s degree is preferred but not mandatory.
* No specific certifications required.