Alpha Researcher / ML Feature Engineer at BHFT

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

16 Dec, 25

Salary

0.0

Posted On

17 Sep, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Science, Python, Quantitative Research, Feature Engineering, Signal Generation, Backtesting, Collaboration, Data Sourcing, Data Cleaning, Predictive Modeling, High-Frequency Trading, Medium-Frequency Trading, Statistical Analysis, Algorithm Development, Market Analysis

Industry

Financial Services

Description

Company Description BHFT is a proprietary algorithmic trading firm. Our team manages the full trading cycle, from software development to creating and coding strategies and algorithms. Our trading operations cover key exchanges. The firm trades across a broad range of asset classes, including equities, equity derivatives, options, commodity futures, rates futures, etc. We employ a diverse and growing array of algorithmic trading strategies, utilizing both High-Frequency Trading (HFT) and Medium-Frequency Trading (MFT) approaches. Looking ahead, we are expanding into new markets and products. As a dynamic company, we continuously experiment with new markets, tools, and technologies. We’ve got a team of 200+ professionals, with a strong emphasis on technology—70% are technical specialists in development, infrastructure, testing, and analytics spheres. The remaining part of the team supports our business operations, such as Risks, Compliance, Legal, Operations and more. Our employees are located all around the world, from the United States to Hong Kong. Although we maintain office spaces, we currently operate as a 100% remote organization. At BHFT, clarity and transparency are at the core of our culture: we value open communication, ensuring that our processes are straightforward. Job Description We are seeking an experienced ML-driven Alpha Researcher / Feature Engineer who thrives at the intersection of fast-paced markets, data science, and collaboration. This role is ideal for someone who can move quickly from idea to execution—transforming complex datasets into predictive trading signals that capture short-term market opportunities. You’ll work alongside a highly skilled modeling and execution team, ensuring that your research ideas don’t stay in theory but turn into real, monetized strategies. Key Responsibilities: Perform rigorous, time-sensitive applied research across diverse data sources—including high-frequency market data and alternative datasets—to uncover systematic anomalies. Design and engineer predictive features that can be rapidly tested and deployed into production strategies. Lead and contribute to end-to-end signal research workflows: data sourcing, cleaning, feature engineering, signal generation, backtesting, and validation. Partner closely with modeling and execution teams to ensure signals are integrated, stress-tested, and monetized efficiently. Qualifications Bachelor, Master’s or PhD in Applied Mathematics, Statistics, Physics, Engineering, Financial Engineering, Computer Science, or related field from a top-tier institution. 5+ years of quantitative research experience with systematic strategies in liquid markets (equities, futures, options); intraday trading expertise is strongly preferred. Proven ability to deliver alpha: signals that translate to real trading profits, not just backtest curves. Expert-level Python skills (Pandas, SciPy, NumPy, Polars); ability to write clean, efficient, and scalable code. Strong collaborative mindset: thrives in team environments, communicates clearly, and moves fast without compromising rigor. High sense of ownership, urgency, and accountability. Additional Information What we offer: Experience a modern international technology company without the burden of bureaucracy. Collaborate with industry-leading professionals, including former employees of Tower, DRW, Broadridge, Credit Suisse, and more. Enjoy excellent opportunities for professional growth and self-realization. Work remotely from anywhere in the world with a flexible schedule. Receive compensation for health insurance, sports activities, and non-professional training.

Responsibilities

Perform rigorous applied research across diverse data sources to uncover systematic anomalies. Design and engineer predictive features for rapid testing and deployment into production strategies.