Quantitative Researcher

Job Title: Quantitative Researcher

Company: Block River Technologies

Location: Remote/Hybrid

Company Overview

Block River Technologies is a quantitative research and technology firm. Block River Technologies develops advanced mathematical models and innovative technology solutions to analyze global financial markets. Its founders have extensive experience in the financial industry and advanced degrees in science, technology, engineering, and mathematics from the world’s leading universities.

We are currently seeking talented, articulate, highly-motivated candidates who will contribute to the design, development, and maintenance of automated trading systems, quantitative research tools, high-performance data management systems, portfolio management tools, and technical architecture/infrastructure.

The responsibilities of new hires will span a wide variety of programming, data analysis, statistical and other quantitative projects. These projects often range in duration and programming environment. This position will have a high degree of autonomy as well as responsibility in the design, direction, and approach in these tasks.

We believe in a casual and collaborative atmosphere in which the candidate can become an integral part of a smaller team. This position allows for a high degree of freedom as well as the ability to be actively involved in the solutions to a variety of challenging problems. While the work is rigorous and demands a high level of commitment, the firm maintains an open, cooperative and collegial atmosphere.

Job Responsibilities

• Develop quantitative trading strategies using statistical models to capture market inefficiencies

• Assist senior strategists in research and management of quantitative strategies

• Build algorithms, models, and tools to:

o Facilitate quantitative research and production trading

o Analyze/manage large data sets to improve profitability

o Evaluate and optimize trading strategies and signals

o Implement quantitative methodologies for portfolio optimization and risk management

o Test hypotheses about markets and simulate trading strategies

• Research and backtest trading strategies in areas such as:

o Basis trading

o CTA / trend-following

o Volatility trading (e.g., covered calls, gamma scalping)

• Evaluate new methodologies and technologies to improve research and production trading environments, system performance, and functionalities

• Generate reports to explain quantitative research results to management and evaluate strategy risk/performance

• Maintain technical documentation of procedures, models, and programming work

• Operate, troubleshoot, and debug software in a fast-paced environment

Job Qualifications

• Proficiency in Python (numpy, pandas/Polars, backtesting libraries)

• Strong foundation in:

o Probability theory, statistics, stochastic processes, time series analysis

o Linear algebra, optimization, and algorithms

o Derivatives: futures basis, options pricing, Greeks, implied volatility

• Strong problem-solving and debugging skills (can analyze and fix problems quickly)

• Ability to prioritize multiple tasks and deliver results in a fast-paced environment

• Strong communication skills: can clearly describe quantitative concepts at both high level (strategy idea) and low level (step-by-step implementation)

• Capable of working independently as well as part of a team

• Degree in a quantitative field: mathematics, statistics, econometrics, operations research, computer science, engineering, or physics

• Optional:

o Prior experience in the financial industry and familiarity with the financial markets are not required

o Interest in quantitative trading as demonstrated by coursework, track record, or work experience is a plus but not required

o Familiarity to research principles, backtesting methods, machine learning, and data issues is a plus but not required

Compensation (including salary, bonus, and incentives/upside) is negotiable based on your skills, education, experience, and performance, reflecting our commitment to recognizing and rewarding your individual contributions.

To apply, please email your cover letter and resume to: [email protected]